Triple

T16769675
Position Surface form Disambiguated ID Type / Status
Subject Kisan language E407558 entity
Predicate hasSpeakersIn P16679 FINISHED
Object Simdega district E791846 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: Simdega district | Statement: [Kisan language, hasSpeakersIn, Simdega district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simdega district
Context triple: [Kisan language, hasSpeakersIn, Simdega district]
  • A. Simdega district chosen
    Simdega district is an administrative region in the Indian state of Jharkhand known for its significant indigenous population and use of tribal languages such as Kharia.
  • B. Sidhi district
    Sidhi district is an administrative district in the Indian state of Madhya Pradesh, known for its coal mining areas and part of the Singrauli region.
  • C. Samastipur district
    Samastipur district is an administrative region in the Indian state of Bihar, known for its agricultural economy and cultural use of the Maithili language.
  • D. Durg district
    Durg district is an administrative district in the state of Chhattisgarh, India, known for its industrial development and urban centers such as the city of Durg.
  • E. Satna district
    Satna district is an administrative district in the Indian state of Madhya Pradesh, known for its cement industries and proximity to important 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0356a9c8190b316cd00223e7537 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf92b148190825778809bc4aac2 completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:21 a.m.