Triple

T13849518
Position Surface form Disambiguated ID Type / Status
Subject KRS Reservoir E332896 entity
Predicate nearCity P350 FINISHED
Object Mandya E1050942 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: Mandya | Statement: [KRS Reservoir, nearCity, Mandya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandya
Context triple: [KRS Reservoir, nearCity, Mandya]
  • A. Mandya city chosen
    Mandya city is an urban center in the Indian state of Karnataka, known for its sugarcane cultivation and role as the administrative and commercial hub of Mandya district.
  • B. Mandya district
    Mandya district is an administrative district in the southern Indian state of Karnataka, known for its fertile agricultural lands and historic towns such as Srirangapatna and Mandya.
  • C. Ramanagara
    Ramanagara is a town in the Indian state of Karnataka, known for its silk industry and rocky hills, and for being a major shooting location for the film "Sholay."
  • D. Kundapura
    Kundapura is a coastal town in the Udupi district of Karnataka, India, known for its temples, beaches, and distinct regional culture.
  • E. Chikkodi
    Chikkodi is a prominent town in Karnataka, India, known for its agricultural economy—especially sugarcane cultivation—and its role as a local commercial and educational hub.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd27f8f388819096c7c33b90f9ac4c completed May 8, 2026, 12:02 a.m.
Created at: April 9, 2026, 10:14 p.m.