---
title: "The NomBank Project: An Interim Report — Meyers 2004"
description: "NomBank tackles a gap in corpus resources. Verbs in the Penn Treebank II already had predicate-argument annotation through PropBank, but common nouns did…"
authors: ["Adam Meyers", "Ruth Reeves", "Catherine Macleod", "Rachel Szekely", "Veronika Zielinska", "Brian Young", "Ralph Grishman"]
year: 2004
venue: "Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004"
source: "https://aclanthology.org/W04-2705/"
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/meyers-2004-nombank-project-interim-report/"
---
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# The NomBank Project: An Interim Report

**Authors:** [Adam Meyers](https://md.research.elamur.ai/free/en/authors/adam-meyers/), Ruth Reeves, Catherine Macleod, [Rachel Szekely](https://md.research.elamur.ai/free/en/authors/rachel-szekely/), Veronika Zielinska, Brian Young, [Ralph Grishman](https://md.research.elamur.ai/free/en/authors/ralph-grishman/) · **Year:** 2004 · **Venue:** Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004 · **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/W04-2705/) · [PDF](https://aclanthology.org/W04-2705.pdf) · [OpenAlex](https://openalex.org/W131863957)

**Citations:** 301 citations (openalex-snapshot · 2026-10-14) · [136](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
NomBank tackles a gap in corpus resources. Verbs in the Penn Treebank II already had predicate-argument annotation through PropBank, but common nouns did not. The project labels argument structure for about 5000 noun predicates, reusing PropBank's numbered roles (ARG0–ARG4), its adjunct types (ARGM-*) and its tooling. It adds SUPPORT items: verbs such as "made" in "made a decision" that connect arguments outside the NP to the noun.

To prepare the work, the team merged COMLEX Syntax, NOMLEX and Levin's verb classes into a new dictionary, NOMLEX-PLUS. They used it to sort nouns into classes and to generate draft frames automatically. Some drafts were converted from PropBank verb entries, others came from class templates, and annotators then corrected them.

Quality control relies on automatic checks that send only suspicious instances back for a second look. This interim report describes the specifications, the workflow and planned future work. Because nouns and verbs share one role scheme, a system can treat phrasings like "IBM appointed John" and "IBM's appointment of John" as the same event. Noun argument structure had previously received little attention.

## Key points
- Target: argument structure for roughly 5000 common nouns in Penn Treebank II. Labels are REL, SUPPORT, ARG0–ARG4 and ARGM types, shared with PropBank.
- NOMLEX-PLUS holds the original 1000 NOMLEX entries plus 6000 new ones. Its classes include verbal nominalizations, adjectival nominalizations and 16 further classes, such as relational and partitive nouns.
- Staffing: one supervisor and one annotator for the first nine months while the specifications were settled, later growing to four annotators.
- Error detection uses several automatic checks:
  - argument nominalizations checked against NOMLEX-PLUS (e.g., *acquirer* = ARG0)
  - required and illegal labels
  - unlikely role configurations, such as a duplicated role
  - wrong-POS detection via GLARF tools
- About 5–10% of instances are flagged for a second pass. Planned next is a rule-based PROPBANKER for automatic annotation, in contrast to statistical systems like Gildea and Jurafsky (2002).

## Interesting ideas
- **"À la carte" layered annotation:** each linguistic layer is defined by its own annotated data over the same corpus. Tools for mapping between layers can then be built and swapped independently, which would also suit a growing multi-layer Ukrainian corpus.
- **Bootstrapping frames from related resources:** draft noun entries were derived automatically from verb frames, and from "cousin" verbs that are semantically similar but morphologically unrelated (e.g., *advantage* modeled on *exploit*). Humans only edit the drafts, which saves lexicographic effort when extending a resource to a new word class.
- **Class-level template frames:** for nouns with no verbal source, one frame is written per noun class and inherited by every member, with per-word fixes. This cheaply covers a long tail of vocabulary.
- **Linguistically motivated sanity checks:** constraints like "the same role should not appear twice", or rare positional patterns, flag likely errors. Re-checking only that small flagged subset keeps quality control affordable.
- **Imperfect automation still has value:** even an automatic annotator too weak to serve as a preprocessor can expose human errors, because disagreements with the manual labels point to instances worth reviewing.

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

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/)

Topics: [Semantic role labeling](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/)

## Cited by

Cited by

136 papers of our library cite it (of the 140673 whose bibliographies we read); 20 of them have a page here, 116 not yet.

- [Automatic Propbank Generation for Turkish](https://md.research.elamur.ai/free/en/papers/ak-2019-automatic-propbank-generation-turkish/)
- [Abstract Meaning Representation for Sembanking](https://md.research.elamur.ai/free/en/papers/banarescu-2013-abstract-meaning-representation-sembanking/)
- [The First Surface Realisation Shared Task: Overview and Evaluation Results](https://md.research.elamur.ai/free/en/papers/belz-2011-first-surface-realisation-shared-task/)
- [Renewing and Revising SemLink](https://md.research.elamur.ai/free/en/papers/bonial-2013-renewing-revising-semlink/)
- [PropBank: Semantics of New Predicate Types](https://md.research.elamur.ai/free/en/papers/bonial-2014-propbank-semantics-new-predicate-types/)
- [Frame-Semantic Parsing](https://md.research.elamur.ai/free/en/papers/das-2014-frame-semantic-parsing/)
- [A Distributional and Orthographic Aggregation Model for English Derivational Morphology](https://md.research.elamur.ai/free/en/papers/deutsch-2018-distributional-orthographic-aggregation-model-english/)
- [VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/fabio-2019-verbatlas-novel-large-scale-verbal/)
- [Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language](https://md.research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/)
- [Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics](https://md.research.elamur.ai/free/en/papers/hershcovich-2020-comparison-conversion-reverse-engineering-ucca/)
- [QANom: Question-Answer driven SRL for Nominalizations](https://md.research.elamur.ai/free/en/papers/klein-2020-qanom-question-answer-driven-srl/)
- [Towards Semi-Automated Annotation for Prepositional Phrase Attachment](https://md.research.elamur.ai/free/en/papers/lingbulk-2010-rosenthal-semi-automated-annotation-prepositional-phrase/)
- [Crowdsourcing Question-Answer Meaning Representations](https://md.research.elamur.ai/free/en/papers/michael-2018-crowdsourcing-question-answer-meaning-representations/)
- [The First Multilingual Surface Realisation Shared Task (SR'18): Overview and Evaluation Results](https://md.research.elamur.ai/free/en/papers/mille-2018-first-multilingual-surface-realisation-shared/)
- [Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation](https://md.research.elamur.ai/free/en/papers/mille-2018-underspecified-universal-dependency-structures-as/)
- [PropBank Comes of Age—Larger, Smarter, and more Diverse](https://md.research.elamur.ai/free/en/papers/pradhan-2022-propbank-comes-age-larger-smarter/)
- [Merging PropBank, NomBank, TimeBank, Penn Discourse Treebank and Coreference](https://md.research.elamur.ai/free/en/papers/pustejovsky-2005-merging-propbank-nombank-timebank-penn/)
- [Meaning Representation of English Prepositional Phrase Roles: SNACS Supersenses vs. Tectogrammatical Functors](https://md.research.elamur.ai/free/en/papers/scivetti-2023-meaning-representation-english-prepositional-phrase/)
- [The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies](https://md.research.elamur.ai/free/en/papers/surdeanu-2008-conll-2008-shared-task-joint/)
- [Semantic Dependency Parsing of NomBank and PropBank: An Efficient Integrated Approach via a Large-scale Feature Selection](https://md.research.elamur.ai/free/en/papers/zhao-2009-semantic-dependency-parsing-nombank-propbank/)

## Cite

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

```bibtex
@inproceedings{meyers2004nombank,
  title = {{The NomBank Project: An Interim Report}},
  author = {Meyers, Adam and Reeves, Ruth and Macleod, Catherine and Szekely, Rachel and Zielinska, Veronika and Young, Brian and Grishman, Ralph},
  booktitle = {Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004},
  year = {2004},
  url = {https://aclanthology.org/W04-2705/}
}
```

- [← previous The MULI Project: Annotation and Analysis of Information Structure in German and English](https://md.research.elamur.ai/free/en/papers/baumann-2004-muli-project-annotation-analysis-information/)
- [next → The Penn Discourse Treebank](https://md.research.elamur.ai/free/en/papers/miltsakaki-2004-penn-discourse-treebank/)
- [↑ back to papers of 2004](https://md.research.elamur.ai/free/en/papers/2004/)

## References

21 references, 3 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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