Triple

T9959275
Position Surface form Disambiguated ID Type / Status
Subject Spanish Army of Africa E195524 entity
Predicate garrisonLocation P40 FINISHED
Object Tetuán E639934 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: Tetuán | Statement: [Spanish Army of Africa, garrisonLocation, Tetuán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tetuán
Context triple: [Spanish Army of Africa, garrisonLocation, Tetuán]
  • A. Tetuán chosen
    Tetuán is a station on the Madrid Metro network serving the Tetuán district in the north of Spain’s capital.
  • B. El Azbakeya
    El Azbakeya is a historic district in central Cairo known for its cultural landmarks, markets, and longstanding role as an urban hub of the city.
  • C. El Ejido
    El Ejido is a major agricultural town in southeastern Spain, renowned for its extensive greenhouse farming and intensive fruit and vegetable production.
  • D. Xàtiva
    Xàtiva is a historic town in the Valencian Community of Spain, known for its medieval castle, rich cultural heritage, and role as the birthplace of the Borgia family.
  • E. Arganzuela district
    Arganzuela district is a central district of Madrid, Spain, known for its mix of residential neighborhoods, cultural venues, and proximity to the Manzanares River.
  • 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_69d23d867b408190ab630ae4af0fb827 completed April 5, 2026, 10:46 a.m.
Created at: March 30, 2026, 8:46 p.m.