Triple

T21965234
Position Surface form Disambiguated ID Type / Status
Subject Dhrol E542439 entity
Predicate hasNearbyCity P350 FINISHED
Object Jamnagar NE NERFINISHED

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: Jamnagar | Statement: [Dhrol, hasNearbyCity, Jamnagar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamnagar
Context triple: [Dhrol, hasNearbyCity, Jamnagar]
  • A. Jamnagar chosen
    Jamnagar is a city in the Indian state of Gujarat, known for its oil refineries, brass industries, and proximity to the Gulf of Kutch.
  • B. Bhadohi
    Bhadohi is a city in Uttar Pradesh, India, renowned as a major center for carpet weaving and often referred to as the "Carpet City" of the country.
  • C. Devendranagar
    Devendranagar is a town in the Panna district of Madhya Pradesh, India, known as a local commercial and residential hub for surrounding rural areas.
  • D. 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.
  • E. Yamunanagar
    Yamunanagar is an industrial city in the Indian state of Haryana, known for its plywood, paper, and metal industries and its proximity to the Yamuna River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1245aabf88190a44564e6eaaa94ce completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8:01 p.m.