Triple

T4753136
Position Surface form Disambiguated ID Type / Status
Subject Buddhist Monuments at Sanchi E105523 entity
Predicate near P350 FINISHED
Object Vidisha E114006 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: Vidisha | Statement: [Buddhist Monuments at Sanchi, near, Vidisha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vidisha
Context triple: [Buddhist Monuments at Sanchi, near, Vidisha]
  • A. Vidisha chosen
    Vidisha is a historic city in the central Indian state of Madhya Pradesh, known for its ancient Buddhist and Hindu heritage and archaeological sites.
  • B. Harda
    Harda is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its agricultural economy and railway connectivity.
  • C. Barwani
    Barwani is a town in the Indian state of Madhya Pradesh, known for its proximity to the Narmada River and its surrounding hilly, forested landscape.
  • D. 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.
  • E. 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.
  • 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_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64e72d1c81908eb60960751e52b1 completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a6600e481909c3fb1decf23d7d8 completed March 21, 2026, 6:27 a.m.
Created at: March 20, 2026, 1:20 p.m.