Triple

T27378887
Position Surface form Disambiguated ID Type / Status
Subject Vitória S.C. E691158 entity
Predicate nickname P55 FINISHED
Object Vitória de Guimarães
Vitória de Guimarães is a Portuguese professional football club based in the city of Guimarães, known for its passionate fanbase and regular presence in the Primeira Liga.
E1804286 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: Vitória de Guimarães | Statement: [Vitória S.C., nickname, Vitória de Guimarães]
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: Vitória de Guimarães
Triple: [Vitória S.C., nickname, Vitória de Guimarães]
Generated description
Vitória de Guimarães is a Portuguese professional football club based in the city of Guimarães, known for its passionate fanbase and regular presence in the Primeira Liga.

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_69ef52022538819081f873d0c84a6dd6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c84610481909e65995538e8faea completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d773f2408190ba9348c1972bb483 completed May 26, 2026, 5:25 p.m.
NEDg Description generation batch_6a15d82ac0fc819082a575f3f11f25da completed May 26, 2026, 5:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15d8e229e88190aaf00c672b1bf5da completed May 26, 2026, 5:31 p.m.
Created at: April 27, 2026, 12:22 p.m.