Triple

T14271733
Position Surface form Disambiguated ID Type / Status
Subject Navsari district E353802 entity
Predicate hasTown P847 FINISHED
Object Bilimora E970205 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: Bilimora | Statement: [Navsari district, hasTown, Bilimora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bilimora
Context triple: [Navsari district, hasTown, Bilimora]
  • A. Bilimora chosen
    Bilimora is a town in the Navsari district of Gujarat, India, known as a regional commercial and transportation hub in South Gujarat.
  • B. Kadamtala
    Kadamtala is a small settlement located on Middle Andaman Island in the Andaman and Nicobar Islands of India.
  • C. Mohanchoti
    Mohanchoti is an island located within Lake Pichola in Udaipur, Rajasthan, India.
  • D. Belpahar
    Belpahar is a small industrial town in the Jharsuguda district of Odisha, India, known for its coal mining and related industries.
  • E. Lagodekhi
    Lagodekhi is a town in eastern Georgia known as a regional center near the Azerbaijani border and as the gateway to the Lagodekhi Protected Areas in the Kakheti region.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de65811d7c8190b075909a6570d415 completed April 14, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd326a5aec8190b139a0c49fd43705 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:10 a.m.