Triple

T13721825
Position Surface form Disambiguated ID Type / Status
Subject Southern Spain E329055 entity
Predicate hasCity P316 FINISHED
Object Almería E66860 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: Almería | Statement: [Southern Spain, hasCity, Almería]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almería
Context triple: [Southern Spain, hasCity, Almería]
  • A. Almería chosen
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • B. Almeria
    Almeria is a coastal municipality on Biliran Island in the Philippines known for its scenic beaches and rural landscapes.
  • C. Jumilla
    Jumilla is a Spanish wine region in the province of Murcia, renowned for its robust red wines, particularly those made from the Mourvèdre (Monastrell) grape.
  • D. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • E. Jaén
    Jaén is a province in southern Spain’s Andalusia region, renowned for its vast olive groves and historic Renaissance towns.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de01f3b46481909ceedfa78e9ca92b completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd3239c3bc8190a6838fe8f2f016bf completed May 8, 2026, 12:45 a.m.
Created at: April 9, 2026, 9:55 p.m.