Triple

T1916066
Position Surface form Disambiguated ID Type / Status
Subject Bundelkhand E40019 entity
Predicate hasCity P316 FINISHED
Object Chhatarpur E136267 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: Chhatarpur | Statement: [Bundelkhand, hasCity, Chhatarpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chhatarpur
Context triple: [Bundelkhand, hasCity, Chhatarpur]
  • A. Chhatarpur chosen
    Chhatarpur is a city in central India known as an administrative and commercial center in the Bundelkhand region of Madhya Pradesh.
  • B. Tikamgarh
    Tikamgarh is a town and administrative center in central India, known for its historical forts and temples in the state of Madhya Pradesh.
  • C. Anuppur
    Anuppur is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to coal mining areas and natural attractions.
  • D. Bilaspur
    Bilaspur is a major city in the Indian state of Chhattisgarh, known as an important administrative, commercial, and judicial center.
  • E. Chhindwara
    Chhindwara is a prominent city in central India known for its agricultural produce, tribal culture, and growing industrial and educational hubs within Madhya Pradesh.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1e517e8819086e4bf5a305aeb25 completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbae5760819083c046d0941513de completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:35 p.m.