Triple

T28166167
Position Surface form Disambiguated ID Type / Status
Subject Palacio de Villalón E715330 entity
Predicate hasOwner P347 FINISHED
Object Municipality of Málaga
The Municipality of Málaga is the local government authority responsible for administering the city of Málaga in southern Spain, overseeing its public services, cultural institutions, and urban development.
E1805663 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: Municipality of Málaga | Statement: [Palacio de Villalón, hasOwner, Municipality of Málaga]
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: Municipality of Málaga
Triple: [Palacio de Villalón, hasOwner, Municipality of Málaga]
Generated description
The Municipality of Málaga is the local government authority responsible for administering the city of Málaga in southern Spain, overseeing its public services, cultural institutions, and urban development.

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_69efd6b340f0819095680e15dcdc1830 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64232c51c8190822b454b225e2af4 completed May 2, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d7b79658819090fb7ccde5f5bd1d completed May 26, 2026, 5:26 p.m.
NEDg Description generation batch_6a15d86ffd208190a771d413e65f8af8 completed May 26, 2026, 5:29 p.m.
NED2 Entity disambiguation (via description) batch_6a15dac9497c8190b12b0088d9907ce5 completed May 26, 2026, 5:39 p.m.
Created at: April 27, 2026, 10:09 p.m.