Triple

T15278021
Position Surface form Disambiguated ID Type / Status
Subject Kuwait Bay E365193 entity
Predicate adjacentTo P224 FINISHED
Object Jahra E95324 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: Jahra | Statement: [Kuwait Bay, adjacentTo, Jahra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jahra
Context triple: [Kuwait Bay, adjacentTo, Jahra]
  • A. Jahra chosen
    Jahra is a major town and administrative center in western Kuwait, known historically as an agricultural area and now as a growing suburban and commercial hub.
  • B. Kherrata
    Kherrata is a town in northeastern Algeria known for being one of the centers of the 1945 anti-colonial unrest that was brutally repressed by French authorities.
  • C. Artouz
    Artouz is a town in southwestern Syria located near Damascus within the Rif Dimashq region.
  • D. Bhamdoun
    Bhamdoun is a Lebanese mountain town and popular summer resort known for its scenic views, cool climate, and historic role as a holiday destination near Beirut.
  • E. Jezzine
    Jezzine is a town in southern Lebanon known for its strategic hilltop location, historic significance, and surrounding pine forests and waterfalls.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00953bc848190b83919f39d5ee37b completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef734f488190951d029183d456f5 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:14 a.m.