Triple

T9576929
Position Surface form Disambiguated ID Type / Status
Subject Haridwar district E231067 entity
Predicate legislativeAssemblyConstituencies P23217 FINISHED
Object Jwalapur E811000 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: Jwalapur | Statement: [Haridwar district, legislativeAssemblyConstituencies, Jwalapur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jwalapur
Context triple: [Haridwar district, legislativeAssemblyConstituencies, Jwalapur]
  • A. Jwalapur chosen
    Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
  • B. Brahmapuri
    Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
  • C. Dantapura
    Dantapura was an ancient city traditionally identified as the royal and administrative center of the Kalinga kingdom in eastern India.
  • D. Karanpur
    Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
  • E. Igatpuri
    Igatpuri is a hill town and railway junction in Maharashtra, India, known for its scenic Western Ghats setting and as a key stop on the route between Mumbai and central/eastern India.
  • 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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99ac17a48190bb8448394f22b1e9 completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1821797f88190b427ad1fcfc73757 completed April 4, 2026, 9:26 p.m.
Created at: March 30, 2026, 8:05 p.m.