Triple

T8250764
Position Surface form Disambiguated ID Type / Status
Subject LAWA E192950 entity
Predicate shortName P43 FINISHED
Object LAWA E192950 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: LAWA | Statement: [LAWA, shortName, LAWA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LAWA
Context triple: [LAWA, shortName, LAWA]
  • A. LAWA chosen
    LAWA is the municipal agency that owns and operates Los Angeles’ system of airports, including Los Angeles International Airport (LAX).
  • B. LAU
    LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
  • C. WLA
    WLA is an acronym commonly used for the Women's Land Army, a civilian organization of women who worked in agriculture to support food production during wartime, particularly in the United Kingdom.
  • D. LAWASIA
    LAWASIA is a regional association of legal professionals and bar organizations in the Asia-Pacific dedicated to promoting the rule of law, human rights, and legal cooperation.
  • E. Sidlaws
    The Sidlaws are a range of rolling hills in eastern Scotland, north of the River Tay, known for their scenic landscapes and popular walking routes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78c935408190b9196a849a8d3a3e completed March 31, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd353888208190941d1c0b7b911cdd completed April 1, 2026, 3:09 p.m.
Created at: March 30, 2026, 5:48 p.m.