Learning to Jointly Predict Ellipsis and Comparison Structures

Abstract

Domain-independent meaning representation of text has received a renewed interest in the NLP community. Comparison plays a crucial role in shaping objective and subjective opinion and measurement in natural language, and is often expressed in complex constructions including ellipsis. In this paper, we introduce a novel framework for jointly capturing the semantic structure of comparison and ellipsis constructions. Our framework models ellipsis and comparison as interconnected predicate-argument structures, which enables automatic ellipsis resolution. We show that a structured prediction model trained on our dataset of 2,800 gold annotated review sentences yields promising results. Together with this paper we release the dataset and an annotation tool which enables two-stage expert annotation on top of tree structures.

Towards Broad-coverage Meaning Representation: The Case of Comparison Structures

“…Earlier, we had experimented with annotating semantic structures on OntoNotes dataset (Bakhshandeh and Allen, 2015). Recently (Bakhshandeh et al, 2016), We have shifted our focus to actual product and restaurant reviews, which include many natural comparison instances. For this purpose we mainly use Google English Web Treebank 4 which comes with gold constituency parse trees.…”

“…We consider two main categories of comparison predicates (Bakhshandeh and Allen, 2015;Bakhshandeh et al, 2016), Ordering and Extreme, each of which can grade any of the four parts of speech including adjectives, adverbs, nouns, and verbs.…”

“…The details of the Extreme type can be found in the earlier work (Bakhshandeh and Allen, 2015;Bakhshandeh et al, 2016).…”

Apples to Apples: Learning Semantics of Common Entities Through a Novel Comprehension Task

“…Various properties of entities can be associated with an abstract scale, such as 'size' or 'sweetness', on which dif- ferent entities can be compared. In order to extract such scales and the relative standing of items on them we use the structured prediction model presented in Bakhshandeh et al (2016), which given a sentence predicts its comparison structures. Figure 8 shows an example predicate-argument structure that is predicted by this model.…”

“…Figure 8 shows an example predicate-argument structure that is predicted by this model. We use pretrained model on the annotated corpus (Bakhshandeh et al, 2016) of comparison structures. Given a comparison structure such as the one presented in Figure 8, we can extract the information that on the scale of 'sweetness' X is higher than Y.…”