Triple

T14875294
Position Surface form Disambiguated ID Type / Status
Subject Financial District, Hyderabad E349851 entity
Predicate locatedNear P294 FINISHED
Object Kokapet E349853 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: Kokapet | Statement: [Financial District, Hyderabad, locatedNear, Kokapet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kokapet
Context triple: [Financial District, Hyderabad, locatedNear, Kokapet]
  • A. Kokapet chosen
    Kokapet is a rapidly developing suburban locality in the western part of Hyderabad, India, known for its emerging IT, commercial, and residential hubs.
  • B. Kalapet
    Kalapet is a coastal locality in the Union Territory of Puducherry, India, known for hosting the main campus of Pondicherry University.
  • C. Kerepehi
    Kerepehi is a small rural town in New Zealand’s North Island, situated in the Hauraki Plains area of the Waikato region.
  • D. Marapu
    Marapu is the indigenous ancestral belief system of the Sumbanese people, characterized by animism, ancestor worship, and elaborate ritual practices.
  • E. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • 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_69fe6b52c12481908d0173a2a3ed854b completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.