Triple

T26063316
Position Surface form Disambiguated ID Type / Status
Subject Andries van Wesel E657327 entity
Predicate employer P7 FINISHED
Object University of Padua E31600 NE 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: University of Padua | Statement: [Andries van Wesel, employer, University of Padua]

Provenance (3 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_69ee5bbd788481909e22bd7153d0c037 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f606954f288190bcb77d432ed3617c completed May 2, 2026, 2:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f7614a88190a63b66cb7950032a completed May 23, 2026, 11:28 a.m.
Created at: April 26, 2026, 7:20 p.m.