Azad Abad


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Self-Crowdsourcing Training for Relation Extraction
Azad Abad | Moin Nabi | Alessandro Moschitti
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

In this paper we introduce a self-training strategy for crowdsourcing. The training examples are automatically selected to train the crowd workers. Our experimental results show an impact of 5% Improvement in terms of F1 for relation extraction task, compared to the method based on distant supervision.


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Taking the best from the Crowd:Learning Question Passage Classification from Noisy Data
Azad Abad | Alessandro Moschitti
Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics


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A Resource for Investigating the Impact of Anaphora and Coreference on Inference.
Azad Abad | Luisa Bentivogli | Ido Dagan | Danilo Giampiccolo | Shachar Mirkin | Emanuele Pianta | Asher Stern
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Discourse phenomena play a major role in text processing tasks. However, so far relatively little study has been devoted to the relevance of discourse phenomena for inference. Therefore, an experimental study was carried out to assess the relevance of anaphora and coreference for Textual Entailment (TE), a prominent inference framework. First, the annotation of anaphoric and coreferential links in the RTE-5 Search data set was performed according to a specifically designed annotation scheme. As a result, a new data set was created where all anaphora and coreference instances in the entailing sentences which are relevant to the entailment judgment are solved and annotated.. A by-product of the annotation is a new “augmented” data set, where all the referring expressions which need to be resolved in the entailing sentences are replaced by explicit expressions. Starting from the final output of the annotation, the actual impact of discourse phenomena on inference engines was investigated, identifying the kind of operations that the systems need to apply to address discourse phenomena and trying to find direct mappings between these operation and annotation types.