---
title: "Analyzing Coordinate Structures Including Punctuation in English"
description: "Coordinate structures (CSs) make English parsing hard. Cited by 1 paper here. Among them: 3."
authors: ["Sadao Kurohashi"]
year: 1995
venue: "Proceedings of the Fourth International Workshop on Parsing Technologies"
source: "https://aclanthology.org/1995.iwpt-1.17/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/kurohashi-1995-analyzing-coordinate-structures-including-punctuation/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kurohashi-1995-analyzing-coordinate-structures-including-punctuation/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [1995](https://md.research.elamur.ai/free/en/papers/1995/) / Analyzing Coordinate Structures Including Punctuation in English

# Analyzing Coordinate Structures Including Punctuation in English

**Authors:** [Sadao Kurohashi](https://md.research.elamur.ai/free/en/authors/sadao-kurohashi/) · **Year:** 1995 · **Venue:** [Proceedings of the Fourth International Workshop on Parsing Technologies](https://md.research.elamur.ai/free/en/venues/iwpt/) ([International Conference on Parsing Technologies and the IWPT Shared Task on Parsing into Enhanced Universal Dependencies 1995](https://md.research.elamur.ai/free/en/venues/iwpt/1995/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/1995.iwpt-1.17/) · [PDF](https://aclanthology.org/1995.iwpt-1.17.pdf) · [OpenAlex](https://openalex.org/W3037868365)

**Citations:** 3 citations (OpenAlex, 2026-10-14) · 1 in our library, of the 149,439 papers whose bibliographies we read

## Summary
Coordinate structures (CSs) make English parsing hard. Their scope is ambiguous, they tend to appear in long sentences, and commas can mark coordination, enclose parentheticals, or simply separate constituents. Kurohashi adapts his earlier parallelism-based conjunct finder, originally built for Japanese, into a joint analyzer for English that decides comma roles and CS scopes together.

The method works in three steps:
- A small phrase-structure grammar over key expressions (commas, *and*, *or*, *but*) lists every "general structure" (GS), meaning every combination of comma roles and CS nesting.
- For each GS, CSs are resolved from the innermost outward. A dynamic-programming search over a word-similarity matrix finds the most similar left and right word sequences. After each step the sentence is reduced so that outer CSs are compared on simplified text.
- GSs are ranked by summed, weighted scores.

On held-out sentences checked against the Penn Treebank, about 80% of commas were interpreted correctly, and about 80% of CS scopes were detected correctly. This matters because it can guide a full parser on long, real sentences without the explosion of complete parse enumeration.

## Key points
- Commas fall into four roles: strong connector (before *and*/*or* in lists of three or more), weak connector (coordination with no conjunction), parenthesizor, and delimiter.
- Word similarity combines three signals: POS match, exact word match, and closeness in the WordNet hierarchy.
- The path score adds element points, penalizes unbalanced conjunct lengths and boundary symbols inside a conjunct, rewards markers such as *both*, and normalizes by a power of the span length.
- The key-expression pattern ", , and and" alone yields 135 candidate GSs. This growth is still much slower than enumerating full parses.
- n-best POS tags used alone hurt scope detection badly because they produce too many spurious similarities. Merging one-best and n-best tags matched one-best accuracy and fixed some tagger errors.

## Interesting ideas
- Treat punctuation and conjunctions as terminals of a tiny grammar, which lets you cheaply list all possible comma-role and nesting skeletons before doing any detailed analysis.
- Resolve the innermost coordinations first, then collapse them to their first conjunct and delete parentheticals, so that outer conjuncts are compared on a simplified sentence.
- Use parallelism between candidate conjuncts as the main scoring signal, mixing POS, lexical identity and thesaurus distance with a penalty for lopsided lengths.
- Choose the correct coordination scope and the correct POS of nearby words at the same time, feeding the scorer a mix of the best tag and alternative tags.
- Weight evidence by how explicit the signal is: a conjunction counts more than a list comma, which counts more than a bare comma joining clauses.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (tree): Before gparse or the perceptron parser commits, enumerate comma/conjunction skeletons and use them as constraints, or as an explainable reason for each `conj`/`parataxis`/`appos` decision.
- **I2** (tree): A reduce-then-compare pass could re-check `conj` attachments in long sentences and catch cases where nested lists confuse the parser.
- **I3** (learn): A parallelism score could act as an independent witness when silver parsers disagree on coordination scope, breaking ties with a transparent reason.
- **I4** (tokens): When the tagger is unsure near *and*/*or* (e.g. NN vs VB), keep the alternatives and let coordination parallelism pick one, instead of trusting the single best tag.
- **I5** (frames): When splitting coordinated clauses into separate frames, rank splits licensed by weak commas lower and flag them as less certain in the explanation.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works

🧭 Topics (1): [English](https://md.research.elamur.ai/free/en/topics/english/) · 2,263 works

## Cite

Cite as: Sadao Kurohashi. 1995. Analyzing Coordinate Structures Including Punctuation in English. Proceedings of the Fourth International Workshop on Parsing Technologies.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{kurohashi1995analyzing,
  title = {{Analyzing Coordinate Structures Including Punctuation in English}},
  author = {Sadao Kurohashi},
  booktitle = {Proceedings of the Fourth International Workshop on Parsing Technologies},
  year = {1995},
  url = {https://aclanthology.org/1995.iwpt-1.17/}
}
```

- [← previous Predicate-Argument Structure of English Adjectives](https://md.research.elamur.ai/free/en/papers/ikeya-1995-predicate-argument-structure-english-adjectives/)
- [next → Learning English Verb Selection Rules from Hand-made Rules and Translation Examples](https://md.research.elamur.ai/free/en/papers/akba-1995-learning-english-verb-selection-rules/)
- [↑ back to papers of 1995](https://md.research.elamur.ai/free/en/papers/1995/)

*Updated 29 October 2026*
