Triple

T869821
Position Surface form Disambiguated ID Type / Status
Subject Toubkal E18784 entity
Predicate nearestMajorCity P1982 FINISHED
Object Marrakesh E24526 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: Marrakesh | Statement: [Toubkal, nearestMajorCity, Marrakesh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marrakesh
Context triple: [Toubkal, nearestMajorCity, Marrakesh]
  • A. Marrakesh chosen
    Marrakesh is a historic and vibrant city in western Morocco, renowned for its bustling medina, iconic red sandstone architecture, and rich cultural heritage.
  • B. Fès-Meknès
    Fès-Meknès is an administrative region in north-central Morocco that includes the historic imperial cities of Fez and Meknès.
  • C. Rabat
    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.
  • D. Meknes
    Meknes is a historic imperial city in northern Morocco known for its grand gates, monumental architecture, and UNESCO-listed medina.
  • 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_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac811e548190a72b7a10b5ea8665 completed March 1, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c71e7c448190aa128bfaf26daead completed March 4, 2026, 5:46 a.m.
Created at: March 1, 2026, 7:39 p.m.