We create the SPADE (Syntactic Phrase Alignment Dataset for Evaluation) for systematic research on syntactic phrase alignment in paraphrasal sentences. This is the first dataset to shed lights on syntactic and phrasal paraphrases under linguistically motivated grammar. Existing datasets available for evaluation on phrasal paraphrase detection define the unit of phrase as simply sequence of words without syntactic structures due to difficulties caused by the non-homographic nature of phrase correspondences in sentential paraphrases. Different from these, the SPADE provides annotations of gold parse trees by a linguistic expert and gold phrase alignments identified by three annotators. Consequently, 20,276 phrases are extracted from 201 sentential paraphrases, on which 15,721 alignments are obtained that at least one annotator regarded as paraphrases. The SPADE is available at Linguistic Data Consortium for future research on paraphrases. In addition, two metrics are proposed to evaluate to what extent the automatic phrase alignment results agree with the ones identified by humans. These metrics allow objective comparison of performances of different methods evaluated on the SPADE. Benchmarks to show performances of humans and the state-of-the-art method are presented as a reference for future SPADE users.
@InProceedings{ARASE18.502, author = {Yuki Arase and Jun'ichi Tsujii}, title = "{SPADE: Evaluation Dataset for Monolingual Phrase Alignment}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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