Triple

T14872608
Position Surface form Disambiguated ID Type / Status
Subject Hassan I Airport E349786 entity
Predicate locatedIn P40 FINISHED
Object Laayoune E70237 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: Laayoune | Statement: [Hassan I Airport, locatedIn, Laayoune]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laayoune
Context triple: [Hassan I Airport, locatedIn, Laayoune]
  • A. Laayoune chosen
    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.
  • B. Oujda
    Oujda is a major city in northeastern Morocco near the Algerian border, known as an important commercial and cultural center of the region.
  • C. Tiznit
    Tiznit is a historic town in southern Morocco known for its traditional silver jewelry craftsmanship and fortified old medina.
  • D. 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.
  • E. Guelmim
    Guelmim is a city in southern Morocco known as a gateway to the Sahara and a regional center for Saharan trade and culture.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e2c94c8190a16f05ea81701fc1 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5101a48190937a86b6eda79c55 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.