Triple

T14882740
Position Surface form Disambiguated ID Type / Status
Subject Sealdah–Ranaghat line E350039 entity
Predicate serves P98 FINISHED
Object Kalyani E184770 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: Kalyani | Statement: [Sealdah–Ranaghat line, serves, Kalyani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kalyani
Context triple: [Sealdah–Ranaghat line, serves, Kalyani]
  • A. Kalyani chosen
    Kalyani is a planned town in the Nadia district of West Bengal, India, known for its educational institutions, industries, and organized urban layout.
  • B. Kalyani
    Kalyani is a historic city in present-day Karnataka, India, renowned as the royal seat of the Western Chalukya dynasty and a major medieval center of politics and culture.
  • C. Bhagyanagar
    Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
  • D. Janakpurdham
    Janakpurdham is a historic city in southeastern Nepal renowned as a major Hindu pilgrimage site associated with the birthplace of Sita and the grand Janaki Temple.
  • E. Krishnanagar
    Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e7c0e48190af2d68a71130585c completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e8192548190ad268b5804c97060 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:56 a.m.