Triple

T20282600
Position Surface form Disambiguated ID Type / Status
Subject Ajit Singh E503186 entity
Predicate residence P75 FINISHED
Object Baghpat E402444 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: Baghpat | Statement: [Ajit Singh, residence, Baghpat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baghpat
Context triple: [Ajit Singh, residence, Baghpat]
  • A. Baghpat chosen
    Baghpat is a town and district headquarters in the Indian state of Uttar Pradesh, situated near Delhi and known for its agricultural economy and growing integration into the National Capital Region’s urban network.
  • B. Hajipur
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • C. Shahjahanpur
    Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
  • D. Saharanpur
    Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
  • E. Rampur
    Rampur is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768f86448190842389a98b93a918 completed April 20, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0870737ea08190aeffad6ef8d3f301 completed May 16, 2026, 1:26 p.m.
Created at: April 16, 2026, 10:40 a.m.