Triple

T28065904
Position Surface form Disambiguated ID Type / Status
Subject Estadio Marcelo Bielsa E709247 entity
Predicate capacity P1433 FINISHED
Object around 42000 LITERAL FINISHED

How this triple was built (1 step)

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: around 42000 | Statement: [Estadio Marcelo Bielsa, capacity, around 42000]

Provenance (2 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_69ef9b6eb6d88190a3fea236eb0f7bed completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6401b760481908d2dcd69bdfa3392 completed May 2, 2026, 6:19 p.m.
Created at: April 27, 2026, 8:42 p.m.