Triple

T632002
Position Surface form Disambiguated ID Type / Status
Subject Islamic world E15944 entity
Predicate hasCulturalCenter P2412 FINISHED
Object Rabat E8849 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: Rabat | Statement: [Islamic world, hasCulturalCenter, Rabat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rabat
Context triple: [Islamic world, hasCulturalCenter, Rabat]
  • A. Rabat chosen
    Rabat is the capital city of Morocco, located on the Atlantic coast and known for its historic medina, coastal fortifications, and role as a political and administrative center.
  • B. Marrakesh
    Marrakesh is a historic and vibrant city in western Morocco, renowned for its bustling medina, iconic red sandstone architecture, and rich cultural heritage.
  • C. Meknes
    Meknes is a historic imperial city in northern Morocco known for its grand gates, monumental architecture, and UNESCO-listed medina.
  • D. Laayoune
    Laayoune is the largest city and de facto administrative center of Western Sahara, located in the northwest of the disputed territory near the Atlantic coast.
  • E. Agadir
    Agadir is a major coastal city in southwestern Morocco known for its Atlantic beaches, modern resort infrastructure, and role as a key tourist destination.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec2a4c08190bc5c6ce8a10b0967 completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5778b82e8819083fbbedb9c3e340e completed March 2, 2026, 11:42 a.m.
Created at: March 1, 2026, 7:35 p.m.