Triple

T16629946
Position Surface form Disambiguated ID Type / Status
Subject AUDA E404051 entity
Predicate shortName P43 FINISHED
Object AUDA E404051 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: AUDA | Statement: [AUDA, shortName, AUDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AUDA
Context triple: [AUDA, shortName, AUDA]
  • A. AUDA chosen
    AUDA is the urban planning and development authority responsible for overseeing and regulating the growth of the Ahmedabad metropolitan region in Gujarat, India.
  • B. Atuda
    Atuda is an Israeli military-academic reserve program that allows selected recruits to complete higher education before serving in professional roles within the Israel Defense Forces.
  • C. Adûni
    Adûni is the Adûnaic-derived native name for Westron, the Common Speech of Middle-earth in J.R.R. Tolkien’s legendarium.
  • D. Adeia
    Adeia, also known as Eurydice II of Macedon, was a Macedonian queen and political figure active during the turbulent succession struggles following Alexander the Great’s death.
  • E. AUN
    AUN is a private American-style university located in Yola, Nigeria, known for its focus on liberal arts education, technology, and development.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e4db5081908a6085f1bc2d65b8 completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dbc6cf48190879b25e66c9453db completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.