Triple

T1252145
Position Surface form Disambiguated ID Type / Status
Subject Vina Fay Wray E26899 entity
Predicate givenName P17 FINISHED
Object Vina E26899 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: Vina | Statement: [Vina Fay Wray, givenName, Vina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vina
Context triple: [Vina Fay Wray, givenName, Vina]
  • A. Vina chosen
    Vina is an alternate given name of Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • B. Shiyan
    Shiyan is an industrial city in northwestern Hubei, China, best known as a center of automobile manufacturing and as a gateway to the nearby Wudang Mountains.
  • C. Can Tho
    Can Tho is a major city in southern Vietnam and the economic and cultural hub of the Mekong Delta region, known for its bustling floating markets and extensive canal network.
  • D. Maiana
    Maiana is a low-lying coral atoll in the central Pacific nation of Kiribati, known for its traditional village life and vulnerability to sea-level rise.
  • E. Mae Sot
    Mae Sot is a Thai border town in Tak Province known as a major hub for cross-border trade and migration with Myanmar and for its numerous refugee and humanitarian aid organizations.
  • 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_69a49487a9c48190ba9b05348fd1b53f completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf875cf48190b6781d41097ee39b completed March 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93c903488190bcbf1928699bafd2 completed March 7, 2026, 9:08 p.m.
Created at: March 1, 2026, 7:47 p.m.