Triple

T30437161
Position Surface form Disambiguated ID Type / Status
Subject Swedish Film Institute E774339 entity
Predicate affiliation P10 FINISHED
Object Swedish Ministry of Culture E1304651 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: Swedish Ministry of Culture | Statement: [Swedish Film Institute, affiliation, Swedish Ministry of Culture]

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_69f22492d2a88190995ce8745d9becaa completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68695d6f88190b3054a58d16b2cb1 completed May 2, 2026, 11:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2798bddb5c8190834da14a38dfb520 completed June 9, 2026, 4:38 a.m.
Created at: April 29, 2026, 8:07 p.m.