Triple

T14150269
Position Surface form Disambiguated ID Type / Status
Subject Kondapur E350659 entity
Predicate nearbyArea P2064 FINISHED
Object Miyapur E353218 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: Miyapur | Statement: [Kondapur, nearbyArea, Miyapur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miyapur
Context triple: [Kondapur, nearbyArea, Miyapur]
  • A. Miyapur chosen
    Miyapur is a rapidly developing residential and commercial suburb in the northwestern part of Hyderabad, India.
  • B. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • C. Shijuku
    "Shijuku" is a jazz track featured on the album *The Tokyo Blues* by pianist Horace Silver.
  • D. Maizuru
    Maizuru is a coastal city in northern Kyoto Prefecture, Japan, known for its natural harbor, former naval base, and role as a key repatriation port after World War II.
  • E. Kagurazaka
    Kagurazaka is a historic neighborhood in central Tokyo known for its narrow cobblestone streets, traditional ryotei restaurants, and blend of old geisha district charm with modern boutiques and cafes.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6124e23481909e5132a40a1d8624 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf21f8c8819097ff26e6bb345b52 completed May 7, 2026, 6:51 p.m.
Created at: April 10, 2026, 12:56 a.m.