[Paper Review] Efficient Construction of Underspecified Semantics under Massive Ambiguity

Jochen Doerre|ArXiv.org|Jun 26, 1997

Natural Language Processing Techniques8 references5 citations

TL;DR

This paper presents an efficient algorithm for constructing compact, underspecified semantic representations from highly ambiguous syntactic parse forests. By directly processing constraint-based semantic rules within a packed forest structure, the method avoids combinatorial explosion and achieves $O(n^4 \log n)$ time complexity under reasonable grammar constraints, enabling scalable semantic analysis in the face of massive ambiguity.

ABSTRACT

We investigate the problem of determining a compact underspecified semantical representation for sentences that may be highly ambiguous. Due to combinatorial explosion, the naive method of building semantics for the different syntactic readings independently is prohibitive. We present a method that takes as input a syntactic parse forest with associated constraint-based semantic construction rules and directly builds a packed semantic structure. The algorithm is fully implemented and runs in $O(n^4 log(n))$ in sentence length, if the grammar meets some reasonable `normality' restrictions.

Motivation & Objective

• To address the computational intractability of generating full semantic representations for sentences with massive syntactic ambiguity.
• To overcome the combinatorial explosion inherent in independently processing each syntactic reading.
• To develop a method that constructs a compact, shared semantic representation directly from a syntactic parse forest.
• To ensure efficiency and scalability in semantic construction under realistic grammar constraints.

Proposed method

• The method takes as input a syntactic parse forest annotated with constraint-based semantic construction rules.
• It employs a packed forest representation to compactly encode all possible syntactic analyses.
• Semantic unification is performed incrementally across the packed structure, avoiding explicit enumeration of all parse trees.
• The algorithm uses a dynamic programming approach with memoization to avoid redundant computation.
• It enforces grammar normality conditions to ensure polynomial-time complexity.
• The core data structure is a constraint-based semantic forest that incrementally builds a shared representation across ambiguous parses.

Experimental results

Research questions

• RQ1 How can semantic representations be constructed efficiently when a sentence admits a vast number of syntactic analyses?
• RQ2 Can a single, compact semantic structure be built without enumerating all possible syntactic parses?
• RQ3 What algorithmic techniques enable $O(n^4 \log n)$ complexity under realistic grammar assumptions?
• RQ4 How can constraint-based semantic rules be applied uniformly across a packed parse forest?
• RQ5 What structural properties of grammars ensure tractable semantic construction under massive ambiguity?

Key findings

• The proposed algorithm achieves $O(n^4 \log n)$ time complexity in sentence length under reasonable grammar normality restrictions.
• The method avoids the combinatorial explosion of generating semantics for each syntactic reading independently.
• A fully implemented system demonstrates the feasibility of the approach on real-world ambiguous sentences.
• The packed semantic structure enables compact representation by sharing common semantic subcomponents across multiple parses.
• The algorithm supports constraint-based semantic unification directly on the forest, preserving ambiguity while minimizing redundancy.
• The approach is general and applicable to a wide range of underspecified semantic formalisms in computational linguistics.