Triple

T9824168
Position Surface form Disambiguated ID Type / Status
Subject Al Wahat District E238611 entity
Predicate borders P224 FINISHED
Object Al Marj District E767305 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: Al Marj District | Statement: [Al Wahat District, borders, Al Marj District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Al Marj District
Context triple: [Al Wahat District, borders, Al Marj District]
  • A. Al Marj District chosen
    Al Marj District is an administrative region in northeastern Libya, known for its agricultural areas and proximity to the city of Benghazi.
  • B. Al Murabba district
    Al Murabba district is a central neighborhood in Riyadh, Saudi Arabia, known for its cultural and historical significance and major landmarks.
  • C. Al Wahat District
    Al Wahat District is an administrative region in northeastern Libya that includes parts of the country’s oil-rich desert areas and key coastal settlements.
  • D. Ibn Ziad District
    Ibn Ziad District is an administrative district located within Constantine Province in northeastern Algeria.
  • E. Al-Gharraf District
    Al-Gharraf District is an administrative district within Iraq’s Dhi Qar Governorate, centered around the town of Al-Gharraf and the surrounding rural areas.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb316f8948190ada3738787a5cb6a completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc810bac8190a5ff94c0717e7706 completed April 5, 2026, 2:44 a.m.
Created at: March 30, 2026, 8:31 p.m.