Triple

T2005731
Position Surface form Disambiguated ID Type / Status
Subject Btourram E43579 entity
Predicate partOf P40 FINISHED
Object Koura District E229563 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: Koura District | Statement: [Btourram, partOf, Koura District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koura District
Context triple: [Btourram, partOf, Koura District]
  • A. Koura District chosen
    Koura District is an administrative district in the North Governorate of Lebanon, known for its olive groves, agricultural production, and mix of coastal and inland towns.
  • B. Kuse District
    Kuse District is a rural administrative district located in Kyoto Prefecture, Japan, known for its small towns and agricultural landscapes.
  • C. Nam District
    Nam District is an administrative district (gu) of the metropolitan city of Busan in South Korea, known for its coastal location and urban residential areas.
  • D. Tupe District
    Tupe District is a small Andean district in Peru notable for preserving the indigenous Jaqaru language and traditional highland culture.
  • E. Yosa District
    Yosa District is a rural administrative district in northern Kyoto Prefecture, Japan, known for its coastal landscapes along the Sea of Japan and traditional fishing and farming communities.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb898795481909920c1a4c4d62c2d completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2707c074819095f932a67f7b5fb9 completed March 9, 2026, 1:48 a.m.
Created at: March 4, 2026, 7:37 p.m.