Triple

T6017165
Position Surface form Disambiguated ID Type / Status
Subject Lucknow district E133975 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Lucknow city E22159 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: Lucknow city | Statement: [Lucknow district, hasUrbanCenter, Lucknow city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucknow city
Context triple: [Lucknow district, hasUrbanCenter, Lucknow city]
  • A. Lucknow chosen
    Lucknow is the capital city of the Indian state of Uttar Pradesh, renowned for its rich cultural heritage, refined Urdu literature, Awadhi cuisine, and elegant Mughal and colonial-era architecture.
  • B. Kanpur
    Kanpur is a major industrial city in the northern Indian state of Uttar Pradesh, historically significant as a key site of conflict during the Indian Rebellion of 1857.
  • C. Aligarh
    Aligarh is a prominent city in northern India known for its lock industry and as the home of Aligarh Muslim University.
  • D. Meerut
    Meerut is a historic city in the Indian state of Uttar Pradesh, known as the place where the Indian Rebellion of 1857 first erupted against British colonial rule.
  • E. Ghaziabad
    Ghaziabad is a major industrial and residential city in the Indian state of Uttar Pradesh, forming part of the National Capital Region near Delhi.
  • 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_69c0087361a48190905c6b55969852b8 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f8458588190a78aa32cbdbecfb1 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c63849a59881909e32c0271b4beb51 completed March 27, 2026, 7:56 a.m.
Created at: March 22, 2026, 4:06 p.m.