Triple

T13610951
Position Surface form Disambiguated ID Type / Status
Subject Coorg E325184 entity
Predicate contains P35 FINISHED
Object Somwarpet E327008 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: Somwarpet | Statement: [Coorg, contains, Somwarpet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Somwarpet
Context triple: [Coorg, contains, Somwarpet]
  • A. Somwarpet chosen
    Somwarpet is a town in Karnataka’s Kodagu (Coorg) district, known for its coffee plantations, scenic hills, and proximity to popular natural attractions.
  • B. Odensala
    Odensala is a locality within Östersund Municipality in Jämtland County, Sweden, functioning as a residential area near the city of Östersund.
  • C. Svedala
    Svedala is a locality and municipality in southern Sweden, known for its proximity to Malmö and its mix of residential areas, industry, and surrounding farmland.
  • D. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0aa9a1481908c6f92495aff86c6 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ae56e2081909c0fd044ce3730a9 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:50 p.m.