Triple

T25107365
Position Surface form Disambiguated ID Type / Status
Subject Hilbert's first problem E628900 entity
Predicate presentedInCity P4490 FINISHED
Object Paris E568 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: Paris | Statement: [Hilbert's first problem, presentedInCity, Paris]

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_69e2ff3071548190b62d1ac237397197 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f46571d33881909e0dce54f0929239 completed May 1, 2026, 8:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cc1f1288190b7c2be3957d578ef completed May 22, 2026, 1:40 p.m.
Created at: April 18, 2026, 6:26 a.m.