[Corpora-List] RTE-7 CHALLENGE at TAC 2011 - Registration deadline extension

[Danilo Giampiccolo]

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SEVENTH RECOGNIZING TEXTUAL ENTAILMENT CHALLENGE at TAC 2011
       (http://www.nist.gov/tac/2011/RTE/)

Last Call for Participation - TAC Registration Deadline: June 10

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NEW

The registration deadline has been extended from June 3 to June 10

REMINDERS

- A web service to automatically evaluate experiments both on the RTE-7 and RTE-6 Main and Novelty Detection data sets is available at http://celct.fbk.eu/RTE_Eval_WS/eval.php. All are invited to take advantage of this service to assess the output of their own RTE system.

- The Main and Novelty Detection Development sets are available at the RTE-7 Website http://www.nist.gov/tac/2011/RTE/).

- The instructions to obtain the KBP Validation Development data are available at the RTE-7 website (http://www.nist.gov/tac/2011/RTE/registration.html).


THE RTE-7 CHALLENGE - INTRODUCTION

The Recognizing Textual Entailment (RTE) task consists of developing a system that, given two text fragments, can determine whether the meaning of one text is entailed, i.e. can be inferred, from the other text. The task has proved to work as a common framework in which to analyze, compare and evaluate different techniques used in NLP applications to deal with semantic inference.

Since the introduction of the RTE task in 2005, RTE challenges have been organized annually. After three highly successful PASCAL RTE Challenges held in Europe, in 2008 RTE became a track at the Text Analysis Conference (TAC).  During the last years RTE has constantly evolved, in the attempt to apply Textual Entailment to specific application settings and move it towards more realistic scenarios. After experimenting textual entailment recognition on a corpus in the RTE-5 Pilot Search task, in RTE-6 further innovations were introduced. First of all, the task of Recognizing Textual Entailment within a Corpus, a close variant of the RTE-5 Pilot task, replaced the traditional Main task. Furthermore, a Novelty Detection subtask aimed at specifically addressing the needs of the Summarization Update scenario was also proposed, where a system has to detect whether a statement is novel with respect to the content of a prior set of documents. Finally a new Knowledge Base Population (KBP) Validation Pilot, based on the TAC KBP Slot Filling task, was set up in order to investigate the potential utility of RTE systems for Knowledge Base Population.

Encouraged by the positive response obtained so far, the RTE Organizing Committee is glad to launch the Seventh Recognizing Textual  Entailment Challenge at TAC 2011.

Organizations interested in participating in the RTE-7 Challenge are invited to submit a track registration form by June 3, 2011, at the TAC 2011 web site (http://www.nist.gov/tac/2011/).

THE RTE-7 TASKS

In order to ensure the continuity with the previous campaign and allow participants to get acquainted with the novelties introduced for the first time in RTE-6, the same tasks are proposed also in RTE-7 without significant changes, namely:

MAIN TASK - RECOGNIZING TEXTUAL ENTAILMENT WITHIN A CORPUS

In the RTE-7 Main task given a corpus, a hypothesis H, and a set of "candidate" entailing sentences for that H retrieved by Lucene from the corpus, RTE systems are required to identify all the sentences that entail H among the candidate sentences.

The RTE-7 Main data set is based on the data created for the TAC 2008 and 2009 Update Summarization task, consisting of a number of topics, each containing two sets of documents, namely i) Cluster A, made up of the first 10 texts in chronological order of publication date, and ii) Cluster B, made up of the last 10 texts. H's are standalone sentences taken from the TAC Update Summarization corpus, meanwhile candidate entailing sentences (T's) are the 100 top-ranked sentences retrieved for each H by Lucene from the Cluster A corpus, using H verbatim as the search query. While only the subset of the candidate entailing sentences must be judged for entailment, these sentences are not to be considered as isolated texts, but the entire Cluster A corpus, to which the candidate entailing sentences belong, is to be taken into considerationin order to resolve discourse references and appropriately judge the entailment relation.

The example below presents a hypothesis referring to a given topic and some of the entailing sentences found in the subset of candidate sentences:

<H_sentence>Lance Armstrong is a Tour de France winner.</H_sentence>
      <text doc_id="AFP_ENG_20050824.0557" s_id="1" evaluation="YES">Claims
      by a French newspaper that seven-time Tour de France winner Lance
      Armstrong had taken EPO were attacked as unsound and unethical by the
      director of the Canadian laboratory whose tests saw Olympic drug cheat
      Ben Johnson hit with a lifetime ban.</text>
      <text doc_id="AFP_ENG_20050824.0557" s_id="2"
        evaluation="YES">L'Equipe on Tuesday carried a front page story
        headlined "Armstrong's Lie" suggesting the Texan had used the illegal
        blood booster EPO (erythropoeitin) during his first Tour win in
        1999.</text>

The second sentence in the example entails H because "the Texan" and "Tour" can be resolved as "Lance Armstrong" and "Tour the France" respectively, on the basis of the context in which they occur in the Cluster A document.

NOVELTY DETECTION SUBTASK

The Novelty Detection subtask is based on the Main task and is aimed at specifically addressing the interests of the Summarization community, in particular with regard to the Update Summarization task, focusing on detection of novelty in Cluster B documents.

The task consists of judging if the information contained in each H (drawn from the Cluster B documents) is novel with respect to the information contained in the set of Cluster A candidate entailing sentences. If for a given H one or more entailing sentences are found, it means that the content of the H is not new. On the contrary, if no
entailing sentences are detected, it means that the information contained in the H is regarded as novel.

The Novelty Detection task requires the same output format as the Main task - i.e. no additional type of decision is needed. Nevertheless, the Novelty Detection task differs from the Main task in the following  ways:

1) The set of H's is not the same as that of the Main task;
2) The system outputs are scored differently, using specific scoring metrics designed for assessing novelty detection.

The Main and Novelty Detection task guidelines and Development set are available at the RTE-7 Website (http://www.nist.gov/tac/2011/RTE/).

KBP VALIDATION TASK

Based on the TAC Knowledge Base Population (KBP) Slot-Filling task, the KBP validation task is to determine whether a given relation (Hypothesis) is supported in an associated document (Text). Each slot fill that is proposed by a system for the KBP Slot-Filling task would create one evaluation item for the RTE-KBP Validation task: the
Hypothesis would be a simple sentence created from the slot fill, while the Text would be the source document that was cited as supporting the slot fill.

The KBP Validation task guidelines are available at the RTE-7 website (http://www.nist.gov/tac/2011/RTE/), together with the instructions to obtain the Development data
(http://www.nist.gov/tac/2011/RTE/registration.html).

RESOURCE AND TOOL EVALUATION THROUGH ABLATION TESTS

The exploratory effort on resource evaluation, started in RTE-5 and extended to tools in RTE-6 , will be continued also in RTE-7. Ablation tests are required for systems participating in the RTE-7 Main task, in order to collect data to better understand the impact of both knowledge resources and tools used by RTE systems and evaluate their contribution to systems' performance.

In an ablation test, a single resource or tool is removed from or added to a system, which is then rerun. Comparing the results to those obtained by the original system, it is possible to assess the practical contribution given by the individual resource or tool.

More details on ablation tests are given in the Main and Novelty Detection Task guidelines (http://www.nist.gov/tac/2011/RTE/RTE7_Main_NoveltyDetection_Task_Guidelines.pdf).

THE RTE RESOURCE POOL AND THE RTE KNOWLEDGE RESOURCES PAGE  AT ACLwiki
(http://www.aclweb.org/aclwiki/index.php?title=Textual_Entailment_Resource_Pool)

The RTE Resource Pool, set up for the first time during RTE-3, serves as a portal and forum for publicizing and tracking resources, and reporting on their use. All the RTE participants and other members of the NLP community who develop or use relevant resources are encouraged to contribute to this important resource.
The RTE Knowledge Resource page (http://www.aclweb.org/aclwiki/index.php?title=Textual_Entailment_Resource_Pool#Knowledge_Resources ) contains a list of the "standard" RTE resources, which have been selected and exploited majorly in the design of RTE systems during the RTE challenges held so far, together with the links to the locations where they are made available. Furthermore, the results of the ablation tests carried out in RTE-5 and in RTE-6, and their description, is also provided.

PROPOSED RTE-7 SCHEDULE

April 29          KBP Validation task: Release of Development Set
April 29            Main task: Release of Development Set
JUNE 10            DEADLINE FOR TAC 2011 TRACK REGISTRATION
August 17         KBP Validation task: Release of Test Set
August 29           Main task: Release of Test Set
September 8         Main task: Deadline for task submissions
September 15        Main task: Release of individual evaluated results
September 16        KBP Validation task: Deadline for task submissions
September 23        KBP Validation task: Release of individual evaluated results
September 25        Deadline for TAC 2011 workshop presentation proposals
September 29        Main task: Deadline for ablation tests submissions
October 6           Main task: Release of individual ablation test results
October 25          Deadline for systems' reports
November 14-15     TAC 2011 workshop in Gaithersburg, Maryland, USA

TRACK COORDINATORS AND ORGANIZERS:
Luisa Bentivogli, CELCT and FBK, Italy
Peter Clark, Vulcan Inc., USA
Ido Dagan, Bar Ilan University, Israel
Hoa Trang Dang, NIST, USA
Danilo Giampiccolo, CELCT, Italy

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