Triple

T15800123
Position Surface form Disambiguated ID Type / Status
Subject Gerald Durrell E383075 entity
Predicate placeOfBirth P1 FINISHED
Object Jamshedpur E318470 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: Jamshedpur | Statement: [Gerald Durrell, placeOfBirth, Jamshedpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamshedpur
Context triple: [Gerald Durrell, placeOfBirth, Jamshedpur]
  • A. Jamshedpur chosen
    Jamshedpur is a major industrial city in eastern India, best known as the home of Tata Steel and one of the country’s earliest planned company towns.
  • B. Dhanbad
    Dhanbad is a major industrial city in eastern India, widely known as the "Coal Capital of India" for its extensive coal mining operations.
  • C. Bhilai
    Bhilai is an industrial city in central India best known for its large steel plant and planned urban infrastructure.
  • D. Kashipur
    Kashipur is a town in the Udham Singh Nagar district of Uttarakhand, India, known as an important industrial and commercial center in the region.
  • E. Samastipur
    Samastipur is a city in the Indian state of Bihar known as an important railway junction and agricultural trade center in the region.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4e135b08190b736e77bac5e2bff completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa12f92e48190bc2886f4070cfc70 completed May 9, 2026, 9:03 p.m.
Created at: April 10, 2026, 4:48 a.m.