Triple

T4628775
Position Surface form Disambiguated ID Type / Status
Subject Hassan II Mosque E101162 entity
Predicate region P40 FINISHED
Object Casablanca-Settat E89239 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: Casablanca-Settat | Statement: [Hassan II Mosque, region, Casablanca-Settat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Casablanca-Settat
Context triple: [Hassan II Mosque, region, Casablanca-Settat]
  • A. Casablanca-Settat region chosen
    The Casablanca-Settat region is an administrative region in western Morocco that includes the country’s largest city and economic hub, Casablanca, along with surrounding urban and rural areas.
  • B. Benslimane
    Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
  • C. Beni Mellal
    Beni Mellal is a major city in central Morocco known for its agricultural importance and its location at the foot of the Middle Atlas mountains.
  • D. Berrechid
    Berrechid is a rapidly growing city in northwestern Morocco known as an important agricultural and industrial hub within the Casablanca-Settat region.
  • E. Sidi Bennour
    Sidi Bennour is a town and provincial capital in western Morocco known for its agricultural activities, particularly cereal and sugar beet production.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a300e6081909fa9f504aada33ea completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06913b448190be47c002641abd34 completed March 21, 2026, 8:58 p.m.
Created at: March 20, 2026, 1:13 p.m.