Triple

T19769206
Position Surface form Disambiguated ID Type / Status
Subject Cave 16 E474836 entity
Predicate near P350 FINISHED
Object Aurangabad city NE NERFINISHED

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: Aurangabad city | Statement: [Cave 16, near, Aurangabad city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aurangabad city
Context triple: [Cave 16, near, Aurangabad city]
  • A. Aurangabad chosen
    Aurangabad is a historic city in the Indian state of Maharashtra, known for its rich cultural heritage and proximity to UNESCO World Heritage Sites like the Ajanta and Ellora Caves.
  • B. Aurangabad district
    Aurangabad district is an administrative district in the Indian state of Bihar, known for its agricultural economy and location in the Magadh region.
  • C. Aligarh
    Aligarh is a prominent city in northern India known for its lock industry and as the home of Aligarh Muslim University.
  • D. Sardarshahar
    Sardarshahar is a town in the Indian state of Rajasthan known for its historic havelis, temples, and traditional Rajasthani culture.
  • E. Moradabad
    Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51a43a08190956bc6df13c91a77 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65359bb9881908f48282b63a83f2f completed April 20, 2026, 4:24 p.m.
Created at: April 10, 2026, 1:48 p.m.