Evaluating Induced CCG Parsers on Grounded Semantic Parsing
Abstract
We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis. This extrinsic, task-based evaluation provides a unique window to explore the strengths and weaknesses of semantics captured by unsupervised grammar induction systems. We release a new Freebase semantic parsing dataset called SPADES (Semantic PArsing of DEclarative Sentences) containing 93K cloze-style questions paired with answers. We evaluate all our models on this dataset. Our code and data are available at https://github.com/sivareddyg/graph-parser.
- Publication:
-
arXiv e-prints
- Pub Date:
- September 2016
- DOI:
- 10.48550/arXiv.1609.09405
- arXiv:
- arXiv:1609.09405
- Bibcode:
- 2016arXiv160909405B
- Keywords:
-
- Computer Science - Computation and Language;
- Computer Science - Artificial Intelligence
- E-Print:
- EMNLP 2016, Table 2 erratum, Code and Freebase Semantic Parsing data URL