[Corpora-List] SemEval 2016 task 2: Interpretable Semantic Textual Similarity

Eneko Agirre e.agirre at ehu.eus
Thu Sep 24 20:37:09 CEST 2015


[apologies for multiple postings]

Call for Participation

SemEval 2016 Task 2

Interpretable Semantic Textual Similarity (iSTS)

http://alt.qcri.org/semeval2016/task2

Training data released

Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text. Interpretable STS (iSTS) adds an explanatory layer. Given the input (pairs of sentences) participants need first to identify the chunks in each sentence, and then, align chunks across the two sentences, indicating the relation and similarity score of each alignment.

For instance, given the following two sentences (drawn from a corpus of headlines):

12 killed in bus accident in Pakistan

10 killed in road accident in NW Pakistan

A participant system would split the sentence in chunks:

[12] [killed] [in bus accident] [in Pakistan]

[10] [killed] [in road accident] [in NW Pakistan]

And then provide the alignments between chunks, indicating the relation and the similarity score of the alignment, as follows:

[12] <=> [10] : (SIMILAR 4)

[killed] <=> [killed] : (EQUIVALENT 5)

[in bus accident] <=> [in road accident] : (MORE-SPECIFIC 4)

[in Pakistan] <=> [in NW Pakistan] : (MORE-GENERAL 4)

Given such an alignment, an automatic system could explain why the two sentences are very similar but not equivalent, for instance, phrasing the differences as follows:

the first sentence mentions "12" instead of "10",

"bus accident" is more specific than "road accident" and

"Pakistan" is more general than "NW Pakistan" in the second.

While giving such explanations comes naturally to people, constructing algorithms and computational models that mimic human level performance represents a difficult natural language understanding (NLU) problem, with applications in dialogue systems, interactive systems and educational systems.

Please check the task website for more details on chunking, alignment, relation labels and scores.

== Datasets ==

Two datasets are currently covered, comprising pairs of sentences from news headlines and image captions. The pairs are a subset of the datasets released in the STS tasks. Please check the iSTS train dataset for details.

== New in 2016 ==

The 2015 STS task offered a pilot subtask on interpretable STS, which showed that the task is feasible, with high inter-annotator agreement and system scores well above baselines.

For 2016, the pilot subtask has been updated into a standalone task. The restriction to allow only 1:1 alignment has been lifted. Annotation guidelines have been updated, and new training has been released. Please check out http://alt.qcri.org/semeval2016/task2/for more details.

== Participants ==

If you are interested in participating, you should:

join the mailing list for updates at

https://groups.google.com/group/ists-semeval

check the guidelines and train data at

http://alt.qcri.org/semeval2016/task2

register at the semeval website:

http://goo.gl/forms/cGkRocFFph

Note that registration and mailing list management are independent, please do both of them.

== Important dates ==

Train data ready: NOW!

Evaluation start: January 10, 2016

Evaluation end: January 31, 2016

Paper submission due: February 28, 2016 [TBC]

Paper reviews due: March 31, 2016 [TBC]

Camera ready due: April 30, 2016 [TBC]

SemEval workshop: Summer 2016

== Organizers ==

Eneko Agirre, Aitor Gonzalez-Agirre, Iņigo Lopez-Gazpio, Montse Maritxalar, German Rigau and Larraitz Uria.

University of the Basque Country

== Reference ==

Agirre, E. and Banea, C. and Cardie, C. and Cer, D. and Diab, M.

and Gonzalez-Agirre, A. and Guo, W. and Lopez-Gazpio, I. and

Maritxalar, M. and Mihalcea, R. and Rigau, G. and Uria, L. and

Wiebe, J. (2015). SemEval-2015 task 2: Semantic textual similarity,

English, Spanish and pilot on interpretability. In Proceedings of

the 9th International Workshop on Semantic Evaluation (SemEval

2015), June. [http://anthology.aclweb.org/S/S15/S15-2045.pdf]



More information about the Corpora mailing list