Triple

T18877097
Position Surface form Disambiguated ID Type / Status
Subject Karwar Beach E461715 entity
Predicate hasNearbyAttraction P2064 FINISHED
Object Karwar town 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: Karwar town | Statement: [Karwar Beach, hasNearbyAttraction, Karwar town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karwar town
Context triple: [Karwar Beach, hasNearbyAttraction, Karwar town]
  • A. Karwar chosen
    Karwar is a coastal city in the Indian state of Karnataka, known for its beaches, port, and role as a key urban center in the Konkan region.
  • B. Tarapur
    Tarapur is a town in the Anand district of Gujarat, India, known as a local commercial and agricultural center.
  • C. Margao
    Margao is a major commercial and cultural city in South Goa, India, known for its historic Portuguese influence and role as a gateway to nearby beaches.
  • D. Sewri
    Sewri is a neighborhood in Mumbai, India, known for its railway station on the city’s suburban network and its location along the eastern waterfront.
  • E. Dalgaon
    Dalgaon is a town and administrative center located in the Darrang district of the northeastern Indian state of Assam.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3cf0aa0819090991fc9e14910fb completed April 20, 2026, 6:12 a.m.
Created at: April 10, 2026, 11:57 a.m.