Triple

T22660541
Position Surface form Disambiguated ID Type / Status
Subject مقبرة العود E559648 entity
Predicate الموقع P1205 FINISHED
Object منطقة الرياض 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: منطقة الرياض | Statement: [مقبرة العود, الموقع, منطقة الرياض]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: منطقة الرياض
Context triple: [مقبرة العود, الموقع, منطقة الرياض]
  • A. Riyadh Province chosen
    Riyadh Province is a central administrative region of Saudi Arabia that includes the national capital, Riyadh, and serves as a major political and economic hub of the country.
  • B. Al Bahah Region
    Al Bahah Region is a mountainous administrative province in southwestern Saudi Arabia known for its cool climate, forests, and traditional villages.
  • C. Qassim Region
    Qassim Region is a central administrative area of Saudi Arabia known for its agricultural productivity, especially date farming, and its traditional Najdi culture.
  • D. Qatif region
    The Qatif region is a historic, oil-rich coastal area in eastern Saudi Arabia along the Persian Gulf, known for its Shia Muslim communities and ancient trading heritage.
  • E. Rabigh Governorate
    Rabigh Governorate is an administrative region on Saudi Arabia’s Red Sea coast that includes the rapidly developing King Abdullah Economic City and the surrounding urban and coastal areas.
  • 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_69e2454a158c819093b8e35f5045efb6 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1765edf88819086c28525e3c73758 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:07 p.m.