Alexander Koller


2020

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Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data
Emily M. Bender | Alexander Koller
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

The success of the large neural language models on many NLP tasks is exciting. However, we find that these successes sometimes lead to hype in which these models are being described as “understanding” language or capturing “meaning”. In this position paper, we argue that a system trained only on form has a priori no way to learn meaning. In keeping with the ACL 2020 theme of “Taking Stock of Where We’ve Been and Where We’re Going”, we argue that a clear understanding of the distinction between form and meaning will help guide the field towards better science around natural language understanding.

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Predicting Coreference in Abstract Meaning Representations
Tatiana Anikina | Alexander Koller | Michael Roth
Proceedings of the Third Workshop on Computational Models of Reference, Anaphora and Coreference

This work addresses coreference resolution in Abstract Meaning Representation (AMR) graphs, a popular formalism for semantic parsing. We evaluate several current coreference resolution techniques on a recently published AMR coreference corpus, establishing baselines for future work. We also demonstrate that coreference resolution can improve the accuracy of a state-of-the-art semantic parser on this corpus.

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Story Generation with Rich Details
Fangzhou Zhai | Vera Demberg | Alexander Koller
Proceedings of the 28th International Conference on Computational Linguistics

Automatically generated stories need to be not only coherent, but also interesting. Apart from realizing a story line, the text also needs to include rich details to engage the readers. We propose a model that features two different generation components: an outliner, which proceeds the main story line to realize global coherence; a detailer, which supplies relevant details to the story in a locally coherent manner. Human evaluations show our model substantially improves the informativeness of generated text while retaining its coherence, outperforming various baselines.

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Generating Instructions at Different Levels of Abstraction
Arne Köhn | Julia Wichlacz | Álvaro Torralba | Daniel Höller | Jörg Hoffmann | Alexander Koller
Proceedings of the 28th International Conference on Computational Linguistics

When generating technical instructions, it is often convenient to describe complex objects in the world at different levels of abstraction. A novice user might need an object explained piece by piece, while for an expert, talking about the complex object (e.g. a wall or railing) directly may be more succinct and efficient. We show how to generate building instructions at different levels of abstraction in Minecraft. We introduce the use of hierarchical planning to this end, a method from AI planning which can capture the structure of complex objects neatly. A crowdsourcing evaluation shows that the choice of abstraction level matters to users, and that an abstraction strategy which balances low-level and high-level object descriptions compares favorably to ones which don’t.

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Normalizing Compositional Structures Across Graphbanks
Lucia Donatelli | Jonas Groschwitz | Matthias Lindemann | Alexander Koller | Pia Weißenhorn
Proceedings of the 28th International Conference on Computational Linguistics

The emergence of a variety of graph-based meaning representations (MRs) has sparked an important conversation about how to adequately represent semantic structure. MRs exhibit structural differences that reflect different theoretical and design considerations, presenting challenges to uniform linguistic analysis and cross-framework semantic parsing. Here, we ask the question of which design differences between MRs are meaningful and semantically-rooted, and which are superficial. We present a methodology for normalizing discrepancies between MRs at the compositional level (Lindemann et al., 2019), finding that we can normalize the majority of divergent phenomena using linguistically-grounded rules. Our work significantly increases the match in compositional structure between MRs and improves multi-task learning (MTL) in a low-resource setting, serving as a proof of concept for future broad-scale cross-MR normalization.

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Fast semantic parsing with well-typedness guarantees
Matthias Lindemann | Jonas Groschwitz | Alexander Koller
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

AM dependency parsing is a linguistically principled method for neural semantic parsing with high accuracy across multiple graphbanks. It relies on a type system that models semantic valency but makes existing parsers slow. We describe an A* parser and a transition-based parser for AM dependency parsing which guarantee well-typedness and improve parsing speed by up to 3 orders of magnitude, while maintaining or improving accuracy.

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MC-Saar-Instruct: a Platform for Minecraft Instruction Giving Agents
Arne Köhn | Julia Wichlacz | Christine Schäfer | Álvaro Torralba | Joerg Hoffmann | Alexander Koller
Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue

We present a comprehensive platform to run human-computer experiments where an agent instructs a human in Minecraft, a 3D blocksworld environment. This platform enables comparisons between different agents by matching users to agents. It performs extensive logging and takes care of all boilerplate, allowing to easily incorporate new agents to evaluate them. Our environment is prepared to evaluate any kind of instruction giving system, recording the interaction and all actions of the user. We provide example architects, a Wizard-of-Oz architect and set-up scripts to automatically download, build and start the platform.

2019

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Saarland at MRP 2019: Compositional parsing across all graphbanks
Lucia Donatelli | Meaghan Fowlie | Jonas Groschwitz | Alexander Koller | Matthias Lindemann | Mario Mina | Pia Weißenhorn
Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning

We describe the Saarland University submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2019 Conference on Computational Natural Language Learning (CoNLL).

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Semantic Expressive Capacity with Bounded Memory
Antoine Venant | Alexander Koller
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

We investigate the capacity of mechanisms for compositional semantic parsing to describe relations between sentences and semantic representations. We prove that in order to represent certain relations, mechanisms which are syntactically projective must be able to remember an unbounded number of locations in the semantic representations, where nonprojective mechanisms need not. This is the first result of this kind, and has consequences both for grammar-based and for neural systems.

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Compositional Semantic Parsing across Graphbanks
Matthias Lindemann | Jonas Groschwitz | Alexander Koller
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Most semantic parsers that map sentences to graph-based meaning representations are hand-designed for specific graphbanks. We present a compositional neural semantic parser which achieves, for the first time, competitive accuracies across a diverse range of graphbanks. Incorporating BERT embeddings and multi-task learning improves the accuracy further, setting new states of the art on DM, PAS, PSD, AMR 2015 and EDS.

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Graph-Based Meaning Representations: Design and Processing
Alexander Koller | Stephan Oepen | Weiwei Sun
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts

This tutorial is on representing and processing sentence meaning in the form of labeled directed graphs. The tutorial will (a) briefly review relevant background in formal and linguistic semantics; (b) semi-formally define a unified abstract view on different flavors of semantic graphs and associated terminology; (c) survey common frameworks for graph-based meaning representation and available graph banks; and (d) offer a technical overview of a representative selection of different parsing approaches.

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Talking about what is not there: Generating indefinite referring expressions in Minecraft
Arne Köhn | Alexander Koller
Proceedings of the 12th International Conference on Natural Language Generation

When generating technical instructions, it is often necessary to describe an object that does not exist yet. For example, an NLG system which explains how to build a house needs to generate sentences like “build *a wall of height five to your left*” and “now build *a wall on the other side*.” Generating (indefinite) referring expressions to objects that do not exist yet is fundamentally different from generating the usual definite referring expressions, because the new object must be distinguished from an infinite set of possible alternatives. We formalize this problem and present an algorithm for generating such expressions, in the context of generating building instructions within the Minecraft video game.

2018

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AMR dependency parsing with a typed semantic algebra
Jonas Groschwitz | Matthias Lindemann | Meaghan Fowlie | Mark Johnson | Alexander Koller
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

We present a semantic parser for Abstract Meaning Representations which learns to parse strings into tree representations of the compositional structure of an AMR graph. This allows us to use standard neural techniques for supertagging and dependency tree parsing, constrained by a linguistically principled type system. We present two approximative decoding algorithms, which achieve state-of-the-art accuracy and outperform strong baselines.

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Generalized chart constraints for efficient PCFG and TAG parsing
Stefan Grünewald | Sophie Henning | Alexander Koller
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Chart constraints, which specify at which string positions a constituent may begin or end, have been shown to speed up chart parsers for PCFGs. We generalize chart constraints to more expressive grammar formalisms and describe a neural tagger which predicts chart constraints at very high precision. Our constraints accelerate both PCFG and TAG parsing, and combine effectively with other pruning techniques (coarse-to-fine and supertagging) for an overall speedup of two orders of magnitude, while improving accuracy.

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Discovering User Groups for Natural Language Generation
Nikos Engonopoulos | Christoph Teichmann | Alexander Koller
Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue

We present a model which predicts how individual users of a dialog system understand and produce utterances based on user groups. In contrast to previous work, these user groups are not specified beforehand, but learned in training. We evaluate on two referring expression (RE) generation tasks; our experiments show that our model can identify user groups and learn how to most effectively talk to them, and can dynamically assign unseen users to the correct groups as they interact with the system.

2017

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Generating Contrastive Referring Expressions
Martín Villalba | Christoph Teichmann | Alexander Koller
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

The referring expressions (REs) produced by a natural language generation (NLG) system can be misunderstood by the hearer, even when they are semantically correct. In an interactive setting, the NLG system can try to recognize such misunderstandings and correct them. We present an algorithm for generating corrective REs that use contrastive focus (“no, the BLUE button”) to emphasize the information the hearer most likely misunderstood. We show empirically that these contrastive REs are preferred over REs without contrast marking.

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Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Mirella Lapata | Phil Blunsom | Alexander Koller
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers

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Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Mirella Lapata | Phil Blunsom | Alexander Koller
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

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Alto: Rapid Prototyping for Parsing and Translation
Johannes Gontrum | Jonas Groschwitz | Alexander Koller | Christoph Teichmann
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics

We present Alto, a rapid prototyping tool for new grammar formalisms. Alto implements generic but efficient algorithms for parsing, translation, and training for a range of monolingual and synchronous grammar formalisms. It can easily be extended to new formalisms, which makes all of these algorithms immediately available for the new formalism.

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Integrated sentence generation using charts
Alexander Koller | Nikos Engonopoulos
Proceedings of the 10th International Conference on Natural Language Generation

Integrating surface realization and the generation of referring expressions into a single algorithm can improve the quality of the generated sentences. Existing algorithms for doing this, such as SPUD and CRISP, are search-based and can be slow or incomplete. We offer a chart-based algorithm for integrated sentence generation and demonstrate its runtime efficiency.

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A Feature Structure Algebra for FTAG
Alexander Koller
Proceedings of the 13th International Workshop on Tree Adjoining Grammars and Related Formalisms

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Parsing Minimalist Languages with Interpreted Regular Tree Grammars
Meaghan Fowlie | Alexander Koller
Proceedings of the 13th International Workshop on Tree Adjoining Grammars and Related Formalisms

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Coarse-To-Fine Parsing for Expressive Grammar Formalisms
Christoph Teichmann | Alexander Koller | Jonas Groschwitz
Proceedings of the 15th International Conference on Parsing Technologies

We generalize coarse-to-fine parsing to grammar formalisms that are more expressive than PCFGs and/or describe languages of trees or graphs. We evaluate our algorithm on PCFG, PTAG, and graph parsing. While we achieve the expected performance gains on PCFGs, coarse-to-fine does not help for PTAG and can even slow down parsing for graphs. We discuss the implications of this finding.

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A constrained graph algebra for semantic parsing with AMRs
Jonas Groschwitz | Meaghan Fowlie | Mark Johnson | Alexander Koller
IWCS 2017 - 12th International Conference on Computational Semantics - Long papers

2016

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Efficient techniques for parsing with tree automata
Jonas Groschwitz | Alexander Koller | Mark Johnson
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Adaptive Importance Sampling from Finite State Automata
Christoph Teichmann | Kasimir Wansing | Alexander Koller
Proceedings of the SIGFSM Workshop on Statistical NLP and Weighted Automata

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Proceedings of the 12th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+12)
David Chiang | Alexander Koller
Proceedings of the 12th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+12)

2015

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Lexicalization and Generative Power in CCG
Marco Kuhlmann | Alexander Koller | Giorgio Satta
Computational Linguistics, Volume 41, Issue 2 - June 2015

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Semantic Dependency Graph Parsing Using Tree Approximations
Željko Agić | Alexander Koller | Stephan Oepen
Proceedings of the 11th International Conference on Computational Semantics

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Semantic construction with graph grammars
Alexander Koller
Proceedings of the 11th International Conference on Computational Semantics

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Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Alexander Koller | Gabriel Skantze | Filip Jurcicek | Masahiro Araki | Carolyn Penstein Rose
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Graph parsing with s-graph grammars
Jonas Groschwitz | Alexander Koller | Christoph Teichmann
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

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The Impact of Listener Gaze on Predicting Reference Resolution
Nikolina Koleva | Martín Villalba | Maria Staudte | Alexander Koller
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

2014

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Potsdam: Semantic Dependency Parsing by Bidirectional Graph-Tree Transformations and Syntactic Parsing
Željko Agić | Alexander Koller
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

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Generating effective referring expressions using charts
Nikolaos Engonopoulos | Alexander Koller
Proceedings of the INLG and SIGDIAL 2014 Joint Session

2013

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Predicting the Resolution of Referring Expressions from User Behavior
Nikos Engonopoulos | Martín Villalba | Ivan Titov | Alexander Koller
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers
Alexander Koller | Katrin Erk
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers

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Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Short Papers
Alexander Koller | Katrin Erk
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Short Papers

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General binarization for parsing and translation
Matthias Büchse | Alexander Koller | Heiko Vogler
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Incremental, Predictive Parsing with Psycholinguistically Motivated Tree-Adjoining Grammar
Vera Demberg | Frank Keller | Alexander Koller
Computational Linguistics, Volume 39, Issue 4 - December 2013

2012

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Enhancing Referential Success by Tracking Hearer Gaze
Alexander Koller | Konstantina Garoufi | Maria Staudte | Matthew Crocker
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Decomposing TAG Algorithms Using Simple Algebraizations
Alexander Koller | Marco Kuhlmann
Proceedings of the 11th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+11)

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Generation of landmark-based navigation instructions from open-source data
Markus Dräger | Alexander Koller
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

2011

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Learning Script Participants from Unlabeled Data
Michaela Regneri | Alexander Koller | Josef Ruppenhofer | Manfred Pinkal
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

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Combining symbolic and corpus-based approaches for the generation of successful referring expressions
Konstantina Garoufi | Alexander Koller
Proceedings of the 13th European Workshop on Natural Language Generation

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Generation Challenges 2011 Preface
Anja Belz | Albert Gatt | Alexander Koller | Kristina Striegnitz
Proceedings of the 13th European Workshop on Natural Language Generation

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Report on the Second Second Challenge on Generating Instructions in Virtual Environments (GIVE-2.5)
Kristina Striegnitz | Alexandre Denis | Andrew Gargett | Konstantina Garoufi | Alexander Koller | Mariët Theune
Proceedings of the 13th European Workshop on Natural Language Generation

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The Potsdam NLG systems at the GIVE-2.5 Challenge
Konstantina Garoufi | Alexander Koller
Proceedings of the 13th European Workshop on Natural Language Generation

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A Generalized View on Parsing and Translation
Alexander Koller | Marco Kuhlmann
Proceedings of the 12th International Conference on Parsing Technologies

2010

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Generation Challenges 2010 Preface
Anja Belz | Albert Gatt | Alexander Koller
Proceedings of the 6th International Natural Language Generation Conference

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Report on the Second NLG Challenge on Generating Instructions in Virtual Environments (GIVE-2)
Alexander Koller | Kristina Striegnitz | Andrew Gargett | Donna Byron | Justine Cassell | Robert Dale | Johanna Moore | Jon Oberlander
Proceedings of the 6th International Natural Language Generation Conference

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Sentence Generation as Planning with Probabilistic LTAG
Daniel Bauer | Alexander Koller
Proceedings of the 10th International Workshop on Tree Adjoining Grammar and Related Frameworks (TAG+10)

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Computing Weakest Readings
Alexander Koller | Stefan Thater
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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The Importance of Rule Restrictions in CCG
Marco Kuhlmann | Alexander Koller | Giorgio Satta
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Learning Script Knowledge with Web Experiments
Michaela Regneri | Alexander Koller | Manfred Pinkal
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Automated Planning for Situated Natural Language Generation
Konstantina Garoufi | Alexander Koller
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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The GIVE-2 Corpus of Giving Instructions in Virtual Environments
Andrew Gargett | Konstantina Garoufi | Alexander Koller | Kristina Striegnitz
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present the GIVE-2 Corpus, a new corpus of human instruction giving. The corpus was collected by asking one person in each pair of subjects to guide the other person towards completing a task in a virtual 3D environment with typed instructions. This is the same setting as that of the recent GIVE Challenge, and thus the corpus can serve as a source of data and as a point of comparison for NLG systems that participate in the GIVE Challenge. The instruction-giving data we collect is multilingual (45 German and 63 English dialogues), and can easily be extended to further languages by using our software, which we have made available. We analyze the corpus to study the effects of learning by repeated participation in the task and the effects of the participants' spatial navigation abilities. Finally, we present a novel annotation scheme for situated referring expressions and compare the referring expressions in the German and English data.

2009

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Report on the First NLG Challenge on Generating Instructions in Virtual Environments (GIVE)
Donna Byron | Alexander Koller | Kristina Striegnitz | Justine Cassell | Robert Dale | Johanna Moore | Jon Oberlander
Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

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Validating the web-based evaluation of NLG systems
Alexander Koller | Kristina Striegnitz | Donna Byron | Justine Cassell | Robert Dale | Sara Dalzel-Job | Johanna Moore | Jon Oberlander
Proceedings of the ACL-IJCNLP 2009 Conference Short Papers

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A Logic of Semantic Representations for Shallow Parsing
Alexander Koller | Alex Lascarides
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

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Dependency Trees and the Strong Generative Capacity of CCG
Alexander Koller | Marco Kuhlmann
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

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The Software Architecture for the First Challenge on Generating Instructions in Virtual Environments
Alexander Koller | Donna Byron | Justine Cassell | Robert Dale | Johanna Moore | Jon Oberlander | Kristina Striegnitz
Proceedings of the Demonstrations Session at EACL 2009

2008

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Regular Tree Grammars as a Formalism for Scope Underspecification
Alexander Koller | Michaela Regneri | Stefan Thater
Proceedings of ACL-08: HLT

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Efficient Processing of Underspecified Discourse Representations
Michaela Regneri | Markus Egg | Alexander Koller
Proceedings of ACL-08: HLT, Short Papers

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Referring Expressions as Formulas of Description Logic
Carlos Areces | Alexander Koller | Kristina Striegnitz
Proceedings of the Fifth International Natural Language Generation Conference

2007

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Sentence generation as a planning problem
Alexander Koller | Matthew Stone
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

2006

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An Improved Redundancy Elimination Algorithm for Underspecified Representations
Alexander Koller | Stefan Thater
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

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Proceedings of the Fifth International Workshop on Inference in Computational Semantics (ICoS-5)
Johan Bos | Alexander Koller
Proceedings of the Fifth International Workshop on Inference in Computational Semantics (ICoS-5)

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Towards a redundancy elimination algorithm for underspecified descriptions
Alexander Koller | Stefan Thater
Proceedings of the Fifth International Workshop on Inference in Computational Semantics (ICoS-5)

2005

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Efficient Solving and Exploration of Scope Ambiguities
Alexander Koller | Stefan Thater
Proceedings of the ACL Interactive Poster and Demonstration Sessions

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The Evolution of Dominance Constraint Solvers
Alexander Koller | Stefan Thater
Proceedings of Workshop on Software

2004

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Minimal Recursion Semantics as Dominance Constraints: Translation, Evaluation, and Analysis
Ruth Fuchss | Alexander Koller | Joachim Niehren | Stefan Thater
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

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Computing Locally Coherent Discourses
Ernst Althaus | Nikiforos Karamanis | Alexander Koller
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

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A Relational Syntax-Semantics Interface Based on Dependency Grammar
Ralph Debusmann | Denys Duchier | Alexander Koller | Marco Kuhlmann | Gert Smolka | Stefan Thater
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Talking robots with Lego MindStorms
Alexander Koller | Geert-Jan Kruijff
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

2003

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Underspecification formalisms: Hole semantics as dominance constraints
Alexander Koller | Joachim Niehren | Stefan Thater
10th Conference of the European Chapter of the Association for Computational Linguistics

2002

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Generation as Dependency Parsing
Alexander Koller | Kristina Striegnitz
Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

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Natural Language and Inference in a Computer Game
Malte Gabsdil | Alexander Koller | Kristina Striegnitz
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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Underspecified Beta Reduction
Manuel Bodirsky | Katrin Erk | Alexander Koller | Joachim Niehren
Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics

2000

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On Underspecified Processing of Dynamic Semantics
Alexander Koller | Joachim Niehren
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

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A Polynomial-Time Fragment of Dominance Constraints
Alexander Koller | Kurt Mehlhorn | Joachim Niehren
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics