Triple

T19731359
Position Surface form Disambiguated ID Type / Status
Subject Faizabad division E473860 entity
Predicate hasSettlement P1068 FINISHED
Object Faizabad NE NERFINISHED

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: Faizabad | Statement: [Faizabad division, hasSettlement, Faizabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faizabad
Context triple: [Faizabad division, hasSettlement, Faizabad]
  • A. Faizabad chosen
    Faizabad is a historic city in the Indian state of Uttar Pradesh that once served as the capital of the former princely state of Oudh (Awadh).
  • B. Faizabad
    Faizabad is a city in northeastern Afghanistan that served as the main stronghold and administrative center of the anti-Taliban government during the late 1990s.
  • C. Mauzamabad
    Mauzamabad is a village-level settlement located within the Jaipur district of the Indian state of Rajasthan.
  • D. Khairabad
    Khairabad is a town in northern India historically known as a center of Islamic scholarship and Urdu and Persian literary culture.
  • E. Khuldabad
    Khuldabad is a historic town in Maharashtra, India, renowned as the burial site of the Mughal emperor Aurangzeb and several prominent Sufi saints.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e649fd18148190a6e85b2be0069dde completed April 20, 2026, 3:45 p.m.
Created at: April 10, 2026, 1:47 p.m.