Triple

T18165426
Position Surface form Disambiguated ID Type / Status
Subject وادي عربة E434879 entity
Predicate قريب من P350 FINISHED
Object مدينة العقبة 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: مدينة العقبة | Statement: [وادي عربة, قريب من, مدينة العقبة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: مدينة العقبة
Context triple: [وادي عربة, قريب من, مدينة العقبة]
  • A. Al Rayyan
    Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
  • B. Thuwal
    Thuwal is a small coastal village on the Red Sea in Saudi Arabia known for hosting the King Abdullah University of Science and Technology (KAUST).
  • C. Al-Doha
    Al-Doha is a Palestinian town located in the Bethlehem Governorate of the West Bank.
  • D. Aqaba chosen
    Aqaba is Jordan’s only coastal city, a key Red Sea port and popular resort destination known for its beaches, coral reefs, and strategic location near the borders with Israel, Egypt, and Saudi Arabia.
  • E. Rabigh
    Rabigh is a coastal city on the Red Sea in western Saudi Arabia known for its industrial complexes, port facilities, and proximity to major pilgrimage and trade routes.
  • 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dec71b7881908d123d0cea3adf1f completed April 19, 2026, 1:55 p.m.
Created at: April 10, 2026, 10:30 a.m.