Triple

T15845159
Position Surface form Disambiguated ID Type / Status
Subject Kaira district E384193 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Nadiad E373389 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: Nadiad | Statement: [Kaira district, hasUrbanCenter, Nadiad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadiad
Context triple: [Kaira district, hasUrbanCenter, Nadiad]
  • A. Nadiad chosen
    Nadiad is a city in the Indian state of Gujarat, historically notable as the birthplace of independence leader Sardar Vallabhbhai Patel.
  • B. Raisinghnagar
    Raisinghnagar is a town and administrative center in the northern Indian state of Rajasthan, known for its agricultural economy within the arid region near the India–Pakistan border.
  • C. Randhawa
    Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
  • D. Bathinda
    Bathinda is a major city in southwestern Punjab, India, known as an important agricultural, industrial, and military center with historical forts and thermal power plants.
  • E. Sardarshahar
    Sardarshahar is a town in the Indian state of Rajasthan known for its historic havelis, temples, and traditional Rajasthani culture.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142eb20088190bb45e37ce3291ef2 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa1412c9481909808473e14058033 completed May 9, 2026, 9:04 p.m.
Created at: April 10, 2026, 4:50 a.m.