Triple

T24381619
Position Surface form Disambiguated ID Type / Status
Subject La Zubia E614626 entity
Predicate partOf P40 FINISHED
Object Metropolitan Area of Granada
The Metropolitan Area of Granada is an urban and suburban region in southern Spain centered on the city of Granada, encompassing surrounding municipalities that share its economic, social, and transport networks.
E1638345 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: Metropolitan Area of Granada | Statement: [La Zubia, partOf, Metropolitan Area of Granada]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Metropolitan Area of Granada
Triple: [La Zubia, partOf, Metropolitan Area of Granada]
Generated description
The Metropolitan Area of Granada is an urban and suburban region in southern Spain centered on the city of Granada, encompassing surrounding municipalities that share its economic, social, and transport networks.

Provenance (5 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_69e2d7e362e481909e32fe4ef8269d4f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f293dc0c3c8190ad6de5db50ccbd76 completed April 29, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee61c33c8190afde88acd0e1b959 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0ff02aa7288190b8b79d27010ee173 completed May 22, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff0cecaf48190951f21afea7a103c completed May 22, 2026, 5:59 a.m.
Created at: April 18, 2026, 2:03 a.m.