Triple

T22376402
Position Surface form Disambiguated ID Type / Status
Subject Ganjam district E553160 entity
Predicate hasTown P847 FINISHED
Object Khalikote 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: Khalikote | Statement: [Ganjam district, hasTown, Khalikote]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khalikote
Context triple: [Ganjam district, hasTown, Khalikote]
  • A. Khallikote chosen
    Khallikote is a town in the Indian state of Odisha, known for its cultural heritage and educational institutions, particularly Khallikote University.
  • B. Narayanpur
    Narayanpur is a town located in the Lakhimpur district of the Indian state of Assam.
  • C. Chhatrapur
    Chhatrapur is a town in the Indian state of Odisha that serves as an administrative and commercial center in the region.
  • D. Chilahati
    Chilahati is a town in northern Bangladesh known for its railway station that serves as a key border transit point on the rail link between Bangladesh and India.
  • E. Kohalpur
    Kohalpur is a growing commercial and transportation hub town in southwestern Nepal, known for its strategic location on the East–West Highway.
  • 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_69e11e4c03248190a26a5060ea6973ee completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158285d208190bc7d05d315267995 completed April 29, 2026, 1 a.m.
Created at: April 16, 2026, 8:45 p.m.