Triple

T9705051
Position Surface form Disambiguated ID Type / Status
Subject Nashik Airport E234876 entity
Predicate hasCityServed P3936 FINISHED
Object Nashik E32761 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: Nashik | Statement: [Nashik Airport, hasCityServed, Nashik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nashik
Context triple: [Nashik Airport, hasCityServed, Nashik]
  • A. Nashik chosen
    Nashik is a historic city in the Indian state of Maharashtra, known for its religious significance in Hinduism and as a major center of wine production.
  • B. Nagpur
    Nagpur is a major city in the Indian state of Maharashtra, known as a key political and commercial center and often referred to as the "Orange City" for its famous orange production.
  • C. Pune
    Pune is a major cultural, educational, and IT hub in the western Indian state of Maharashtra, known for its universities, historical significance, and rapidly growing urban economy.
  • D. Nanded
    Nanded is a historic city in the Indian state of Maharashtra, known as an important Sikh pilgrimage center and a major urban hub in the Marathwada region.
  • E. Kolhapur
    Kolhapur is a historic city in the Indian state of Maharashtra, known for its rich Maratha heritage, temples, and distinctive Kolhapuri cuisine and leather sandals.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d74afb4819084174aab5bcdb6e0 completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2cb2aaef481908a7be61bbfc3b008 completed April 5, 2026, 8:50 p.m.
Created at: March 30, 2026, 8:18 p.m.