Triple

T14787884
Position Surface form Disambiguated ID Type / Status
Subject Sitapur district E347574 entity
Predicate hasMunicipality P847 FINISHED
Object Khairabad E1092228 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: Khairabad | Statement: [Sitapur district, hasMunicipality, Khairabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khairabad
Context triple: [Sitapur district, hasMunicipality, Khairabad]
  • A. Khairabad chosen
    Khairabad is a town in northern India historically known as a center of Islamic scholarship and Urdu and Persian literary culture.
  • B. Shikohabad
    Shikohabad is a city in the Indian state of Uttar Pradesh, known for its location along major road and rail routes and its role as a regional commercial center.
  • C. Shahganj
    Shahganj is a town in the Jaunpur district of Uttar Pradesh, India, known as a local commercial and transportation hub for the surrounding rural region.
  • D. Yaseenabad
    Yaseenabad is a residential neighborhood located within the Federal B Area of Karachi, Pakistan.
  • E. Shahpura
    Shahpura is a town in Rajasthan, India, historically known as the administrative and cultural center of the former princely Shahpura State.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decaa083e481908336d58d026eec32 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b4531fc819084d9ab1c86cb540c completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:31 a.m.