Abstract
Natural Language Generation (NLG) is a research task which addresses the automatic generation of natural language text representative of an input non-linguistic collection of knowledge. In this paper, we address the task of the generation of grammatical sentences in an isolated context given a partial bag-of-words which the generated sentence must contain. We view the task as a search problem (a problem of choice) involving combinations of smaller chunk based templates extracted from a training corpus to construct a complete sentence. To achieve that, we propose a fitness function which we use in conjunction with an evolutionary algorithm as the search procedure to arrive at a potentially grammatical sentence (modeled by the fitness score) which satisfies the input constraints.- Anthology ID:
- P18-3017
- Volume:
- Proceedings of ACL 2018, Student Research Workshop
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 120–126
- Language:
- URL:
- https://aclanthology.org/P18-3017
- DOI:
- 10.18653/v1/P18-3017
- Cite (ACL):
- Nikhilesh Bhatnagar, Manish Shrivastava, and Radhika Mamidi. 2018. Exploring Chunk Based Templates for Generating a subset of English Text. In Proceedings of ACL 2018, Student Research Workshop, pages 120–126, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Exploring Chunk Based Templates for Generating a subset of English Text (Bhatnagar et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/P18-3017.pdf