Triple

T7815019
Position Surface form Disambiguated ID Type / Status
Subject North Bengal (India) E180983 entity
Predicate hasCity P316 FINISHED
Object Raiganj E208174 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: Raiganj | Statement: [North Bengal (India), hasCity, Raiganj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raiganj
Context triple: [North Bengal (India), hasCity, Raiganj]
  • A. Raiganj chosen
    Raiganj is a town in northern West Bengal, India, known as the headquarters of Uttar Dinajpur district and for its nearby Raiganj Wildlife Sanctuary.
  • B. Baranagar
    Baranagar is a densely populated suburban city in the northern part of Kolkata, India, known for its industrial areas, educational institutions, and cultural heritage.
  • C. Krishnanagar
    Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
  • D. Ranaghat
    Ranaghat is a prominent town in the Indian state of West Bengal, known as a key railway junction and commercial center in the Nadia region.
  • E. Chalisgaon
    Chalisgaon is a town in the Indian state of Maharashtra known for its railway junction and proximity to historical and religious sites.
  • 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_69ca828153f48190bdb27ac46f8e0745 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf96c009c81909726e1653b6f1348 completed March 30, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cc63967c0c8190aef301575560a927 completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 4:39 p.m.