[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/rudzicz-2010-towards-heuristic-categorization-prepositional-phrases/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [English](https://md.mova.elamur.ai/free/en/docs/papers/en/) / Towards a Heuristic Categorization of Prepositional Phrases in English with WordNet # Towards a Heuristic Categorization of Prepositional Phrases in English with WordNet **Authors:** Frank Rudzicz, Serguei A. Mokhov · **Year:** 2010 · **Venue:** arXiv:1002.1095 (a report first written in 2003) **Link:** [arxiv.org/abs/1002.1095](https://arxiv.org/abs/1002.1095) · **Licence:** arXiv — non-exclusive licence to distribute — summary only [**5** citations](https://openalex.org/works?filter=cites:W1559370477) openalex · 2026-10-18[**2** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rudzicz-2010-towards-heuristic-categorization-prepositional-phrases/) of the 140673 papers whose bibliographies we read[arXiv:1002.1095](https://openalex.org/S4306400194)[licence](http://arxiv.org/licenses/nonexclusive-distrib/1.0/) - [Publisher's page](https://arxiv.org/abs/1002.1095) - [PDF](https://arxiv.org/pdf/1002.1095) - [arXiv 1002.1095](https://arxiv.org/abs/1002.1095) - [OpenAlex](https://openalex.org/W1559370477) **Authors (2)** 1. [Frank Rudzicz](https://openalex.org/A5056256317) [ORCID](https://orcid.org/0000-0002-1139-3423) · h 42 · 7445 citations · 389 works 2. [Serguei A. Mokhov](https://openalex.org/A5047782865) [ORCID](https://orcid.org/0000-0002-8791-4790) · h 17 · 1142 citations · 192 works Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart. ## What it is about The paper builds a rule-based system that finds prepositional phrases (PPs) in parsed text and then gives each one a semantic role from seven classes taken from the Penn Treebank: locative, temporal, directional, manner, purpose, extent and beneficiary. It is organised in levels. Level 0 is a small grammar that finds minimal PPs; Level 1 adds the role labels, using the preposition as a first guess and then the WordNet hypernyms of the head noun, which override the guess. The data are 27 Wall Street Journal documents, of which 20 (about 74%) are used to write the rules and 7 (about 26%) to test them. The final grammar reaches recall 87.8%, precision 85.0% and F 86.4% for PP finding. For the categorisation, the total F is 81.5%; directional PPs reach 89.0% and manner PPs only 63.1%. ## Ideas - I1. `prag/src/roles.rs`: write the role rules over UD trees, with the case marker (`case` relation) as the first cue and the lemma of the head noun's WordNet hypernym as the second, which overrides the first. Keep the rule table in BTreeMap order and log which rule chose each label, so each choice can be explained. - I2. Report precision, recall and F for each role class separately, as the paper does, and keep a "left as bare PP" class, so that unsure cases are not forced into a wrong role. - I3. Use the paper's two-layer design as an ablation: run with the preposition cue only, then with the hypernym layer added. The gain of the second layer is the number to publish. ## For Mova The chapter is [22. Phrases: noun, adjective, adverb and prepositional phrases](https://md.mova.elamur.ai/free/en/docs/languages/en/22-phrases/), with [10. Word classes](https://md.mova.elamur.ai/free/en/docs/languages/en/10-word-classes/) for prepositions. The code is `prag/src/roles.rs` for the role rules and `en/src/dict.rs` for the lexicon of prepositions. The measures: per-class P, R and F on a hand-labelled set of school sentences, a held-out split, and the layer ablation above. The paper's rule-based approach fits Mova; its PP-attachment part is left open there and would be a later step. ## Cite The paper itself, not this card. BibTeX from the library's record of the work. [arXiv 1002.1095](https://arxiv.org/abs/1002.1095) ``` @misc{rudzicz2010heuristic, title = {{Towards a Heuristic Categorization of Prepositional Phrases in English with WordNet}}, author = {Rudzicz, Frank and Mokhov, Serguei A.}, year = {2010}, eprint = {1002.1095}, archivePrefix = {arXiv}, url = {https://arxiv.org/abs/1002.1095} } ``` - [← previous Neural Models of Factuality](https://md.mova.elamur.ai/free/en/docs/papers/rudinger-2018-neural-models-factuality/) - [next → A Dictionary and Morphological Analyser for English](https://md.mova.elamur.ai/free/en/docs/papers/russell-1986-dictionary-morphological-analyser-english/) - [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/) ## References 8 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. EAGLES96. Preliminary Recommendations on Semantic Encod- [OW02] T. O’Hara and J. Wiebe. Classifying Preposition Semantic Roles using Class-based Lexical ing Interim Report. 1996. URL: Associations. 2002. NMSU-CS-2002-001 [http://www.ilc.cnr.it/EAGLES96](http://www.ilc.cnr.it/EAGLES96) URL: www.cs.nmsu.edu/TechReports /rep/node13.html, Nov 23, 2003. /2002/013.pdf. [↗](http://www.ilc.cnr.it/EAGLES96) 2. I. Pratt and N. Francez. On the Seman-tactic Parsing Strategies. University of Con-tics of Temporal Prepositions and Preposition necticut, 1978. PhD thesis. Phrases. University of Manchester, 1997. [find](https://scholar.google.com/scholar?q=I%2E+Pratt+and+N%2E+Francez%2E+On+the+Seman%2Dtactic+Parsing+Strategies%2E+University+of+Con%2Dtics+of+Temporal+Prepositions+and+Preposition+necticut%2C+1978%2E+PhD+thesis%2E+Phrases%2E+University+of+Manchester%2C+1997%2E) 3. N. Francez and M. Steedman. Categori- [Qui85] cal Grammar and the Semantics of Indexical Prepositional Phrases. Human Communication Research Centre, University of Edinburgh, 2003. [find](https://scholar.google.com/scholar?q=N%2E+Francez+and+M%2E+Steedman%2E+Categori%2D+%5BQui85%5D+cal+Grammar+and+the+Semantics+of+Indexical+Prepositional+Phrases%2E+Human+Communication+Research+Centre%2C+University+of+Edinburgh%2C+2003%2E) 4. R.A. Hudson. Phrases. November 2003. www.phon.ucl.ac.uk/home/dick /tta/phrases/phrases.htm#pp. [find](https://scholar.google.com/scholar?q=R%2EA%2E+Hudson%2E+Phrases%2E+November+2003%2E+www%2Ephon%2Eucl%2Eac%2Euk%2Fhome%2Fdick+%2Ftta%2Fphrases%2Fphrases%2Ehtm%23pp%2E) 5. (Eds.). Holt Rinehart and Winston Inc„ 1973. 346-65. [find](https://scholar.google.com/scholar?q=%28Eds%2E%29%2E+Holt+Rinehart+and+Winston+Inc%E2%80%9E+1973%2E+346%2D65%2E) 6. Daniel S. Jurafsky and James H. Martin. [Whi90] G. et al Whittemore. Empirical Study of Pre-Speech and Language Processing. Prentice-dictive Powers of Simple Attachment Schemes Hall, Inc., Pearson Higher Education, Upper for Post-Modifier Prepositional Phrases in Pro-Saddle River, New Jersey 07458, 2000. ISBN ceedings of the 28th Annual Meeting of the As-0-13-095069-6. sociation for Computation Linguistics. 1990. pages 23-30. [find](https://scholar.google.com/scholar?q=Daniel+S%2E+Jurafsky+and+James+H%2E+Martin%2E+%5BWhi90%5D+G%2E+et+al+Whittemore%2E+Empirical+Study+of+Pre%2DSpeech+and+Language+Processing%2E+Prentice%2Ddictive+Powers+of+Simple+Attachment+Schemes+Hall%2C+Inc%2E%2C+Pearson+Hig) 7. J. Kimball. Seven Principals of Surface Structure Parsing in Natural Language. MIT Press, 1973. Cognition 2:15-47. 5 Appendix [find](https://scholar.google.com/scholar?q=J%2E+Kimball%2E+Seven+Principals+of+Surface+Structure+Parsing+in+Natural+Language%2E+MIT+Press%2C+1973%2E+Cognition+2%3A15%2D47%2E+5+Appendix) 8. B. Levin and S. Pinker. Lexical and Concep- 5.1 Appendix A: PP Rule Set tual Semantics. Elsevier Science Publications, The rule set is quite small and simple provided the rest of Amsterdam, 1991. the grammar has a quite a notion of what NP and VP are. C.D. Manning and H. Schutze. Foundations of This basic rule set is used for Level 0 of our work. This Statistical Natural Language Processing. MIT gives us a list of unclassified PPs from a corpus. Later on, Press, 2002. a Perl script run to augment this information with the 7 [find](https://scholar.google.com/scholar?q=B%2E+Levin+and+S%2E+Pinker%2E+Lexical+and+Concep%2D+5%2E1+Appendix+A%3A+PP+Rule+Set+tual+Semantics%2E+Elsevier+Science+Publications%2C+The+rule+set+is+quite+small+and+simple+provided+the+rest+of+Amsterdam%2C+1991%2E+the+)