Triple

T20718524
Position Surface form Disambiguated ID Type / Status
Subject Arkavati E509243 entity
Predicate flowsNear P350 FINISHED
Object Thippagondanahalli NE NERFINISHED

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: Thippagondanahalli | Statement: [Arkavati, flowsNear, Thippagondanahalli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thippagondanahalli
Context triple: [Arkavati, flowsNear, Thippagondanahalli]
  • A. Thippagondanahalli chosen
    Thippagondanahalli is a village in Karnataka, India, best known for the nearby Thippagondanahalli Dam that serves as a major water source for Bengaluru.
  • B. Bommanahalli
    Bommanahalli is a rapidly developing residential and commercial suburb in the southeastern part of Bengaluru, India, known for its proximity to major IT hubs and location along Hosur Road.
  • C. Devanahalli
    Devanahalli is a town near Bengaluru in the Indian state of Karnataka, notable for its rapid development and proximity to Kempegowda International Airport.
  • D. Kundalahalli
    Kundalahalli is a prominent residential and commercial neighborhood in eastern Bengaluru, known for its proximity to IT hubs like Whitefield and Marathahalli.
  • E. Nayandahalli
    Nayandahalli is a locality in southwestern Bangalore known as a key junction and residential area along major transport routes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1d39bec8190b3642b0d6d833375 completed April 21, 2026, 12:16 a.m.
Created at: April 16, 2026, 12:25 p.m.