[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/schubert-1990-picking-reference-events-tense-formal/) [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/) / Picking Reference Events from Tense Trees: A Formal, Implementable Theory of English Tense-Aspect Semantics # Picking Reference Events from Tense Trees: A Formal, Implementable Theory of English Tense-Aspect Semantics **Authors:** Lenhart K. Schubert, Chung Hee Hwang · **Year:** 1990 · **Venue:** Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27, 1990 **Link:** [aclanthology.org/H90-1008](https://aclanthology.org/H90-1008/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) (ACL Anthology, before 2016) — summary only [Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27, 1990](https://aclanthology.org/volumes/H90-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/) - [Publisher's page](https://aclanthology.org/H90-1008/) - [PDF](https://aclanthology.org/H90-1008.pdf) **Authors (2)** 1. Lenhart K. Schubert 2. Chung Hee Hwang Citations and author metrics from OpenAlex (); authors with the same name are not always told apart. ## What it is about The paper turns English tense and aspect into explicit relations between episodes (events and situations) in a formal episodic logic. Each sentence's logical form is first built compositionally, with separate past, present, perfect and future operators. A "tense tree" then serves as context. Each node has a past, a perfect and a future branch, and the focus moves as the operators are met. The rules for present, past, future, perfect and that-clauses rewrite the indexical form into episode variables, with relations such as "before", "orients" and "at-about", and they store the new episode at the focal node. Later inference discharges the "context-charged" relations, for example a default that the next event follows its reference point. The rules are implemented in Common Lisp. The example traces (for instance a sequence of past-tense sentences about John and Mary) come out as the intuitive order, and the example sentences run in about a tenth of a second on a 1990 workstation. The paper reports no accuracy measure. ## Ideas - I1. Use a tense tree as the deterministic store of event order in `world/src/narr.rs`: each event gets a node, and the order a text implies can be read off and checked. Measure it against hand-coded orders from the school lessons. - I2. Implement the two perfect readings (perf1 and perf2) and test the paper's contrast: "John has left yesterday" is out, "John had left the day before" is in. Use these as grammar tests for [13. Verbs](https://md.mova.elamur.ai/free/en/docs/languages/en/13-verbs/). - I3. Store a "why" string with each ordering: the rule that placed the event and the orienting event it used. This is the explanation Mova asks for. - I4. Negative control: scramble the sentence order of a passage. A tree-based ordering must change, and a rule that ignores tense must not. ## For Mova The chapter is [13. Verbs](https://md.mova.elamur.ai/free/en/docs/languages/en/13-verbs/) (with [14. Irregular verbs](https://md.mova.elamur.ai/free/en/docs/languages/en/14-irregular-verbs/) for forms). The code is `en/src/morph.rs` (tense forms), `world/src/narr.rs` and `world/src/events.rs`. The measure is event-order accuracy on a fixed set of passages with gold orders, run twice, with the scrambled-order control above. ## Cite The paper itself, not this card. BibTeX from the library's record of the work. ``` @inproceedings{schubert1990picking, title = {{Picking Reference Events from Tense Trees: A Formal, Implementable Theory of English Tense-Aspect Semantics}}, author = {Schubert, Lenhart K. and Hwang, Chung Hee}, booktitle = {Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27, 1990}, year = {1990}, url = {https://aclanthology.org/H90-1008/} } ``` - [← previous DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations](https://md.mova.elamur.ai/free/en/docs/papers/scholman-2022-discogem-crowdsourced-corpus-genre-mixed/) - [next → Extracting and evaluating general world knowledge from the Brown Corpus](https://md.mova.elamur.ai/free/en/docs/papers/schubert-2003-extracting-evaluating-general-world-knowledge/) - [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/) ## References 19 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. 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