Triple

T16541473
Position Surface form Disambiguated ID Type / Status
Subject Ottoman garrisons in Yemen E401828 entity
Predicate location P40 FINISHED
Object Taiz E113390 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: Taiz | Statement: [Ottoman garrisons in Yemen, location, Taiz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taiz
Context triple: [Ottoman garrisons in Yemen, location, Taiz]
  • A. Taiz chosen
    Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
  • B. Arafo
    Arafo is a small municipality on the island of Tenerife in Spain’s Canary Islands, known for its rural landscapes and traditional Canarian character.
  • C. Qairawan
    Qairawan is a locality within Kuwait’s Al Asimah (Capital) Governorate, forming part of the urban area around Kuwait City.
  • D. Berrechid
    Berrechid is a rapidly growing city in northwestern Morocco known as an important agricultural and industrial hub within the Casablanca-Settat region.
  • E. Hamina
    Hamina is a coastal town and municipality in southeastern Finland known for its historic star-shaped fortress and strategic location on the Gulf of Finland.
  • 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_69d88384bc30819084229e7dcdc39a41 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3455cf4b88190b3c9e93e158a7686 completed April 18, 2026, 8:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ed9fa988190892ca20939080f5f completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:15 a.m.