Triple

T27507354
Position Surface form Disambiguated ID Type / Status
Subject Gran Tarajal E694312 entity
Predicate governedBy P46 FINISHED
Object Ayuntamiento de Tuineje
The Ayuntamiento de Tuineje is the municipal council and local governing body of the town and municipality of Tuineje on the island of Fuerteventura in Spain’s Canary Islands.
E1775763 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: Ayuntamiento de Tuineje | Statement: [Gran Tarajal, governedBy, Ayuntamiento de Tuineje]
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: Ayuntamiento de Tuineje
Triple: [Gran Tarajal, governedBy, Ayuntamiento de Tuineje]
Generated description
The Ayuntamiento de Tuineje is the municipal council and local governing body of the town and municipality of Tuineje on the island of Fuerteventura in Spain’s Canary Islands.

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_69ef53842afc8190ba6bd4e4999bda67 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62ef65ca88190b3e3b1c91d668843 completed May 2, 2026, 5:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbfd5f94819097979c3c041f3c18 completed May 24, 2026, 8:51 a.m.
NEDg Description generation batch_6a12bd205e9c81908e89639719aa4ac2 completed May 24, 2026, 8:56 a.m.
NED2 Entity disambiguation (via description) batch_6a12bdc819e4819090b6ecae640773ab completed May 24, 2026, 8:58 a.m.
Created at: April 27, 2026, 1:14 p.m.