Triple

T14875395
Position Surface form Disambiguated ID Type / Status
Subject Kokapet E349853 entity
Predicate locatedNear P294 FINISHED
Object Narsingi E1085388 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: Narsingi | Statement: [Kokapet, locatedNear, Narsingi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narsingi
Context triple: [Kokapet, locatedNear, Narsingi]
  • A. Narsingi chosen
    Narsingi is a rapidly developing residential and commercial suburb in the western part of Hyderabad, Telangana, known for its proximity to the IT corridor and Outer Ring Road.
  • B. Nagole
    Nagole is a residential and commercial neighborhood in Hyderabad, India, served as a key terminus and transit hub on the Hyderabad Metro network.
  • C. Ghansoli
    Ghansoli is a rapidly developing residential and commercial node in Navi Mumbai, Maharashtra, known for its growing IT parks, educational institutions, and connectivity to Mumbai via rail and road.
  • D. Ramdurg
    Ramdurg is a town in the Indian state of Karnataka, known for its historical temples and its location within the Belagavi region.
  • E. Vallabhnagar
    Vallabhnagar is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the Udaipur region.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e3e5d48190a132f2cf012b01e2 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9687a5888190a6e6ffd781f64edc completed May 9, 2026, 2:05 a.m.
Created at: April 10, 2026, 1:55 a.m.