Triple

T7753908
Position Surface form Disambiguated ID Type / Status
Subject Sibi District E175840 entity
Predicate borderedBy P224 FINISHED
Object Kohlu District E637848 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: Kohlu District | Statement: [Sibi District, borderedBy, Kohlu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kohlu District
Context triple: [Sibi District, borderedBy, Kohlu District]
  • A. Kohlu District chosen
    Kohlu District is an administrative district in the Balochistan province of Pakistan, known for its rugged terrain and predominantly Baloch population.
  • B. Kajaki District
    Kajaki District is an administrative district in northern Helmand Province, Afghanistan, known for the Kajaki Dam and its strategic significance in the region.
  • C. Miura District
    Miura District is a rural administrative district in Kanagawa Prefecture, Japan, known for its coastal towns and scenic Miura Peninsula landscapes.
  • D. Kuse District
    Kuse District is a rural administrative district located in Kyoto Prefecture, Japan, known for its small towns and agricultural landscapes.
  • E. Guichi District
    Guichi District is an urban district that serves as the central administrative and commercial hub of Chizhou in Anhui Province, China.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703d851d4819091e9117d3f34cb9a completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c94db29c248190acf3349adc82656c completed March 29, 2026, 4:05 p.m.
Created at: March 27, 2026, 4:08 p.m.