Triple

T26074416
Position Surface form Disambiguated ID Type / Status
Subject Futebol Clube de Alverca E657640 entity
Predicate homeStadium P890 FINISHED
Object Estádio do FC Alverca
Estádio do FC Alverca is a football stadium in Alverca do Ribatejo, Portugal, primarily used for hosting the home matches of Futebol Clube de Alverca.
E1719582 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: Estádio do FC Alverca | Statement: [Futebol Clube de Alverca, homeStadium, Estádio do FC Alverca]
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: Estádio do FC Alverca
Triple: [Futebol Clube de Alverca, homeStadium, Estádio do FC Alverca]
Generated description
Estádio do FC Alverca is a football stadium in Alverca do Ribatejo, Portugal, primarily used for hosting the home matches of Futebol Clube de Alverca.

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_69ee5bbe539081909efc7f9dd7c1b53c completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f606cde3608190a83c0f258d8b38b7 completed May 2, 2026, 2:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f909fa48190a694c61a7baccac6 completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 26, 2026, 7:32 p.m.