---
title: "NLML — paper by Jia (2004) — summary and ideas"
description: "Jia tackles a practical gap in symbolic English parsing. 17 references, cited by 1 paper here."
authors: ["Jiyou Jia"]
year: 2004
venue: "arXiv:cs/0404018"
source: "https://arxiv.org/abs/cs/0404018"
doi: "10.48550/arxiv.cs/0404018"
arxiv: "cs/0404018"
licence: "arXiv — no licence stated (read only)"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/jia-2004-nlml-markup-language-describe-unlimited/"
---
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# NLML — a Markup Language to Describe the Unlimited English Grammar

**Authors:** [Jiyou Jia](https://md.research.elamur.ai/free/en/authors/jiyou-jia/) · **Year:** 2004 · **Venue:** arXiv:cs/0404018 · **Licence:** arXiv — no licence stated (read only)

**Links:** [Publisher's page](https://arxiv.org/abs/cs/0404018) · [PDF](https://arxiv.org/pdf/cs/0404018) · [DOI 10.48550/arxiv.cs/0404018](https://doi.org/10.48550/arxiv.cs/0404018) · [arXiv cs/0404018](https://arxiv.org/abs/cs/0404018) · [OpenAlex](https://openalex.org/W1564079883)

**Citations:** 6 citations (OpenAlex, 2026-10-14) · [1](https://md.research.elamur.ai/free/en/papers/jia-2004-nlml-markup-language-describe-unlimited/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
Jia tackles a practical gap in symbolic English parsing. Parsers such as an AGFL-generated one produce deeply nested trees whose labels (NP, subject, verb) mean something to linguists but are hard for downstream programs to use. The problem is worst when a sentence holds several verbs or subjects, as in relative clauses. The author's solution is NLML, a tag-based output format produced through AGFL's transduction mechanism. Its context-free grammar draws on the grammar textbooks by Chalker and by Hanks & Grandison. NLML explicitly labels mood, complexity, subjects, verb phrases, tense, person, number, circumstances and clause structure at three levels: sentence, clause and phrase. The paper shows how arbitrary utterances, including dialogue fragments, map onto this markup. It also presents two uses inside the CSIEC language-learning dialogue project. NLOMJ maps the markup onto Java objects, and NLDB stores NLML strings in database tables so earlier discourse can be reloaded without reparsing. The point is a directly queryable, editable and storable representation of grammar for dialogue systems.

## Key points
- NLML is produced by AGFL's transduced output form, not by post-processing the usual indented or bracketed parse tree.
- The top-level `expression` rule lists 16 alternatives covering 11 `<mood>` categories:
  - full-sentence moods: statement, question, order, full exclamation;
  - fragment moods: np, adj, about, circumstances, what/how terse exclamations, subcircum.
- A max-matching priority makes full-sentence readings win, and `$PENALTY` weights push fragment readings down.
- The lexicon is an editable text file that stores word types, affixes and probabilities; AGFL calls the resulting probability-aware parsing hybrid parsing.
- NLOMJ models grammar elements as Java classes using inheritance and association.
- NLDB stores NLML strings in database tables split into facts, questions and fact relations. This supports context analysis for dialogue generation in CSIEC.

## Interesting ideas
- The parser emits a self-describing structure with named slots such as subject, verb word and mood, so a consumer can ask "what is the subject?" without searching the tree; this also resolves ambiguity when there are several clauses.
- Max-matching means trying a full-sentence reading first and only falling back, under explicit penalties, to fragment readings such as a bare NP, adjective or adverbial; this suits dialogue input that is often elliptical.
- Fragments receive both a mood label and their essential content word: "What a pity!" is a terse exclamation whose core is the noun "pity".
- Sentence-level transformations such as negation or statement-to-question are done by editing the structured markup rather than the surface string.
- Analyses are stored as serialized strings, filed by type (facts, questions, relations between facts), and rehydrated later without reparsing.

## For Mova

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

- **I1** (frames): Frames could be exposed as named per-clause slots tied to a specific clause node, so questions about multi-verb sentences return the right predicate's arguments.
- **I2** (tree): Fragments like "Why?" or "That one you have read." could get a scored fallback analysis instead of a forced sentence parse.
- **I3** (frames): Speech-act tagging could pair the act type with its head element, helping link short replies to the previous turn.
- **I4** (back): Generation could implement mood and polarity changes as edits on the meaning graph before realization, making them explainable and testable.
- **I5** (world): Text-world snapshots could be persisted per category so a long discourse can be reloaded and extended cheaply.

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

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

## Cite

Cite as: Jiyou Jia. 2004. NLML — a Markup Language to Describe the Unlimited English Grammar. arXiv:cs/0404018.

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

```bibtex
@misc{jia2004nlml,
  title = {{NLML — a Markup Language to Describe the Unlimited English Grammar}},
  author = {Jiyou Jia},
  year = {2004},
  doi = {10.48550/arxiv.cs/0404018},
  eprint = {cs/0404018},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.cs/0404018}
}
```

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## References

17 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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2. Chalker, S.: Current English grammar. Macmillan Publishers Ltd. (1984) [find](https://scholar.google.com/scholar?q=Chalker%2C+S%2E%3A+Current+English+grammar%2E+Macmillan+Publishers+Ltd%2E+%281984%29)
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14. Tapanainen, P. & Järvinen, T.:. [A non-projective dependency parser](https://md.research.elamur.ai/free/en/papers/tapanainen-1997-non-projective-dependency-parser/). In: Proceedings of the 5th conference on Applied Natural Language Processing (1997). Washington, D.C. 64-71
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*Updated 29 October 2026*