Triple

T5178227
Position Surface form Disambiguated ID Type / Status
Subject Azrou E116852 entity
Predicate hasNearbyCity P350 FINISHED
Object Meknes E47150 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: Meknes | Statement: [Azrou, hasNearbyCity, Meknes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meknes
Context triple: [Azrou, hasNearbyCity, Meknes]
  • A. Meknes chosen
    Meknes is a historic imperial city in northern Morocco known for its grand gates, monumental architecture, and UNESCO-listed medina.
  • B. Fès-Meknès
    Fès-Meknès is an administrative region in north-central Morocco that includes the historic imperial cities of Fez and Meknès.
  • C. Oujda
    Oujda is a major city in northeastern Morocco near the Algerian border, known as an important commercial and cultural center of the region.
  • D. Sefrou
    Sefrou is a historic town in northern Morocco known for its traditional medina, cherry festival, and location near the Middle Atlas mountains.
  • E. Tiznit
    Tiznit is a historic town in southern Morocco known for its traditional silver jewelry craftsmanship and fortified old medina.
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7976339481909ece900de22064f2 completed March 20, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfdeb0d0cc8190a16b8dcff2658bbf completed March 22, 2026, 12:21 p.m.
Created at: March 20, 2026, 1:45 p.m.