Triple

T9959276
Position Surface form Disambiguated ID Type / Status
Subject Spanish Army of Africa E195524 entity
Predicate garrisonLocation P40 FINISHED
Object Larache E220517 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: Larache | Statement: [Spanish Army of Africa, garrisonLocation, Larache]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larache
Context triple: [Spanish Army of Africa, garrisonLocation, Larache]
  • A. Larache chosen
    Larache is a coastal city in northwestern Morocco, situated along the Atlantic Ocean and known for its historic medina and nearby ancient Phoenician-Roman archaeological site of Lixus.
  • B. Tiznit
    Tiznit is a historic town in southern Morocco known for its traditional silver jewelry craftsmanship and fortified old medina.
  • C. Guelmim
    Guelmim is a city in southern Morocco known as a gateway to the Sahara and a regional center for Saharan trade and culture.
  • D. Errachidia
    Errachidia is a city in eastern Morocco that serves as an administrative and commercial hub for the surrounding desert and oasis regions.
  • E. Benslimane
    Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d08fdc8190a77b9c97830035bc completed April 2, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cb77b51481908af779b8ecacc3f1 completed April 5, 2026, 8:52 p.m.
Created at: March 30, 2026, 8:46 p.m.