Álvaro Rodrigo

Also published as: Alvaro Rodrigo


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A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation
Jan Deriu | Katsiaryna Mlynchyk | Philippe Schläpfer | Alvaro Rodrigo | Dirk von Grünigen | Nicolas Kaiser | Kurt Stockinger | Eneko Agirre | Mark Cieliebak
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

In this paper, we introduce a novel methodology to efficiently construct a corpus for question answering over structured data. For this, we introduce an intermediate representation that is based on the logical query plan in a database, called Operation Trees (OT). This representation allows us to invert the annotation process without loosing flexibility in the types of queries that we generate. Furthermore, it allows for fine-grained alignment of the tokens to the operations. Thus, we randomly generate OTs from a context free grammar and annotators just have to write the appropriate question and assign the tokens. We compare our corpus OTTA (Operation Trees and Token Assignment), a large semantic parsing corpus for evaluating natural language interfaces to databases, to Spider and LC-QuaD 2.0 and show that our methodology more than triples the annotation speed while maintaining the complexity of the queries. Finally, we train a state-of-the-art semantic parsing model on our data and show that our dataset is a challenging dataset and that the token alignment can be leveraged to significantly increase the performance.

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Spot The Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems
Jan Deriu | Don Tuggener | Pius von Däniken | Jon Ander Campos | Alvaro Rodrigo | Thiziri Belkacem | Aitor Soroa | Eneko Agirre | Mark Cieliebak
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

The lack of time efficient and reliable evalu-ation methods is hampering the development of conversational dialogue systems (chat bots). Evaluations that require humans to converse with chat bots are time and cost intensive, put high cognitive demands on the human judges, and tend to yield low quality results. In this work, we introduce Spot The Bot, a cost-efficient and robust evaluation framework that replaces human-bot conversations with conversations between bots. Human judges then only annotate for each entity in a conversation whether they think it is human or not (assuming there are humans participants in these conversations). These annotations then allow us to rank chat bots regarding their ability to mimic conversational behaviour of humans. Since we expect that all bots are eventually recognized as such, we incorporate a metric that measures which chat bot is able to uphold human-like be-havior the longest, i.e.Survival Analysis. This metric has the ability to correlate a bot’s performance to certain of its characteristics (e.g.fluency or sensibleness), yielding interpretable results. The comparably low cost of our frame-work allows for frequent evaluations of chatbots during their evaluation cycle. We empirically validate our claims by applying Spot The Bot to three domains, evaluating several state-of-the-art chat bots, and drawing comparisonsto related work. The framework is released asa ready-to-use tool.


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Temporally Anchored Relation Extraction
Guillermo Garrido | Anselmo Peñas | Bernardo Cabaleiro | Álvaro Rodrigo
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Evaluating Machine Reading Systems through Comprehension Tests
Anselmo Peñas | Eduard Hovy | Pamela Forner | Álvaro Rodrigo | Richard Sutcliffe | Corina Forascu | Caroline Sporleder
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes a methodology for testing and evaluating the performance of Machine Reading systems through Question Answering and Reading Comprehension Tests. The methodology is being used in QA4MRE (QA for Machine Reading Evaluation), one of the labs of CLEF. The task was to answer a series of multiple choice tests, each based on a single document. This allows complex questions to be asked but makes evaluation simple and completely automatic. The evaluation architecture is completely multilingual: test documents, questions, and their answers are identical in all the supported languages. Background text collections are comparable collections harvested from the web for a set of predefined topics. Each test received an evaluation score between 0 and 1 using c@1. This measure encourages systems to reduce the number of incorrect answers while maintaining the number of correct ones by leaving some questions unanswered. 12 groups participated in the task, submitting 62 runs in 3 different languages (German, English, and Romanian). All runs were monolingual; no team attempted a cross-language task. We report here the conclusions and lessons learned after the first campaign in 2011.


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A Simple Measure to Assess Non-response
Anselmo Peñas | Alvaro Rodrigo
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies


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GikiCLEF: Crosscultural Issues in Multilingual Information Access
Diana Santos | Luís Miguel Cabral | Corina Forascu | Pamela Forner | Fredric Gey | Katrin Lamm | Thomas Mandl | Petya Osenova | Anselmo Peñas | Álvaro Rodrigo | Julia Schulz | Yvonne Skalban | Erik Tjong Kim Sang
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In this paper we describe GikiCLEF, the first evaluation contest that, to our knowledge, was specifically designed to expose and investigate cultural and linguistic issues involved in structured multimedia collections and searching, and which was organized under the scope of CLEF 2009. GikiCLEF evaluated systems that answered hard questions for both human and machine, in ten different Wikipedia collections, namely Bulgarian, Dutch, English, German, Italian, Norwegian (Bokmäl and Nynorsk), Portuguese, Romanian, and Spanish. After a short historical introduction, we present the task, together with its motivation, and discuss how the topics were chosen. Then we provide another description from the point of view of the participants. Before disclosing their results, we introduce the SIGA management system explaining the several tasks which were carried out behind the scenes. We quantify in turn the GIRA resource, offered to the community for training and further evaluating systems with the help of the 50 topics gathered and the solutions identified. We end the paper with a critical discussion of what was learned, advancing possible ways to reuse the data.

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Evaluating Multilingual Question Answering Systems at CLEF
Pamela Forner | Danilo Giampiccolo | Bernardo Magnini | Anselmo Peñas | Álvaro Rodrigo | Richard Sutcliffe
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The paper offers an overview of the key issues raised during the seven years’ activity of the Multilingual Question Answering Track at the Cross Language Evaluation Forum (CLEF). The general aim of the Multilingual Question Answering Track has been to test both monolingual and cross-language Question Answering (QA) systems that process queries and documents in several European languages, also drawing attention to a number of challenging issues for research in multilingual QA. The paper gives a brief description of how the task has evolved over the years and of the way in which the data sets have been created, presenting also a brief summary of the different types of questions developed. The document collections adopted in the competitions are sketched as well, and some data about the participation are provided. Moreover, the main evaluation measures used to evaluate system performances are explained and an overall analysis of the results achieved is presented.


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Experiments of UNED at the Third Recognising Textual Entailment Challenge
Álvaro Rodrigo | Anselmo Peñas | Jesús Herrera | Felisa Verdejo
Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing