Triple

T16375925
Position Surface form Disambiguated ID Type / Status
Subject Oriental Region E397679 entity
Predicate containsCity P294 FINISHED
Object Oujda E443613 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: Oujda | Statement: [Oriental Region, containsCity, Oujda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oujda
Context triple: [Oriental Region, containsCity, Oujda]
  • A. Oujda chosen
    Oujda is a major city in northeastern Morocco near the Algerian border, known as an important commercial and cultural center of the region.
  • B. 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.
  • C. Aïn M’lila
    Aïn M’lila is a city in northeastern Algeria known as a regional commercial and transportation hub.
  • 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. Cherchell
    Cherchell is a historic coastal town in northern Algeria, known for its ancient Phoenician and Roman heritage and its role as a cultural center in the region.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319d79df8819087285b9457b7bdb6 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f41703c81908fb040a9107045ae completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:08 a.m.