Triple

T12691410
Position Surface form Disambiguated ID Type / Status
Subject Mehrauli E303212 entity
Predicate near P350 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: [Mehrauli, near, Chhatarpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chhatarpur
Context triple: [Mehrauli, near, 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. Pithoragarh
    Pithoragarh is a town and district in the eastern Kumaon region of Uttarakhand, India, known for its scenic Himalayan landscapes and strategic location near the Nepal and Tibet borders.
  • C. Narayanpur
    Narayanpur is a town located in the Lakhimpur district of the Indian state of Assam.
  • D. Karauli
    Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
  • E. Ghatshila
    Ghatshila is a scenic town in Jharkhand, India, known for its forested hills, waterfalls, and literary association with Bengali writer Bibhutibhushan Bandyopadhyay.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961dabb38819087738361f9de8066 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c7a79908190b83a868090990bbe completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:22 p.m.