Triple

T29301446
Position Surface form Disambiguated ID Type / Status
Subject Sathya Movies E742967 entity
Predicate primaryLanguageOfFilms P73189 FINISHED
Object Tamil E6357 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: Tamil | Statement: [Sathya Movies, primaryLanguageOfFilms, Tamil]

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_69f09123ed9881909f351f7541933f5e completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665a2ab44819080b1c5f711c229e4 completed May 2, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a847fc208190b1ed19a536b1663c completed June 7, 2026, 5:20 p.m.
Created at: April 28, 2026, 1:10 p.m.