Triple

T11200260
Position Surface form Disambiguated ID Type / Status
Subject Dollars Trilogy E265019 entity
Predicate filmingLocation P40 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: [Dollars Trilogy, filmingLocation, Almería]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almería
Context triple: [Dollars Trilogy, filmingLocation, 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. 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.
  • D. Jaén
    Jaén is a province in southern Spain’s Andalusia region, renowned for its vast olive groves and historic Renaissance towns.
  • E. Jaén
    Jaén is a significant commercial and agricultural city in northern Peru, known as a regional hub within the Cajamarca Region.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8c1e9f88190b2b42326aba9d778 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e623e44c188190b5b83cf8f397554c completed April 20, 2026, 1:02 p.m.
Created at: April 8, 2026, 9:29 p.m.