Triple

T14293897
Position Surface form Disambiguated ID Type / Status
Subject LB Nagar E354387 entity
Predicate nearbyArea P2064 FINISHED
Object Nagole E354388 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: Nagole | Statement: [LB Nagar, nearbyArea, Nagole]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagole
Context triple: [LB Nagar, nearbyArea, Nagole]
  • A. Nagole chosen
    Nagole is a residential and commercial neighborhood in Hyderabad, India, served as a key terminus and transit hub on the Hyderabad Metro network.
  • B. Lakkundi
    Lakkundi is a historic village in Karnataka, India, renowned for its intricately carved medieval temples and stepwells built during the Western Chalukya period.
  • C. Narsingi
    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.
  • D. Ulhasnagar
    Ulhasnagar is a city in the Mumbai Metropolitan Region of Maharashtra, India, known for its large Sindhi community and extensive furniture and textile markets.
  • E. Narsapur
    Narsapur is a prominent town in Telangana, India, known as one of the major urban centers of Medak district.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de7179368081908117a9ccfbf94fd4 completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7a13288190a73683e275f6bbc0 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:11 a.m.