Triple

T14554536
Position Surface form Disambiguated ID Type / Status
Subject Iraq-i Ajam E341504 entity
Predicate hasMajorCity P316 FINISHED
Object Natanz E1081384 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: Natanz | Statement: [Iraq-i Ajam, hasMajorCity, Natanz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Natanz
Context triple: [Iraq-i Ajam, hasMajorCity, Natanz]
  • A. Natanz chosen
    Natanz is a town in central Iran’s Isfahan Province, known both for its historic architecture and for hosting one of the country’s key nuclear facilities.
  • B. Tandava
    Tandava is the vigorous, cosmic dance of the Hindu god Shiva, symbolizing creation, preservation, and destruction of the universe.
  • C. Tanza
    Tanza is a coastal municipality in the province of Cavite in the Philippines, known for its historical significance and growing residential and industrial communities.
  • D. Judba
    Judba is a small town in Pakistan’s Khyber Pakhtunkhwa province that serves as the administrative and political center of Torghar District.
  • E. Kitri
    Kitri is the spirited village girl and female lead in the classical ballet Don Quixote, renowned for her fiery personality and virtuosic dancing.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f00cec8190a7b6482d18b9a216 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab9a5ac81908779a3c8701353fa completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:23 a.m.