Triple
T33465318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuck Jones Enterprises |
E857026
|
entity |
| Predicate | purpose |
P79
|
FINISHED |
| Object | create works based on Chuck Jones’s characters |
—
|
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: create works based on Chuck Jones’s characters | Statement: [Chuck Jones Enterprises, purpose, create works based on Chuck Jones’s characters]
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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e4f996948190a20e96059d5188cc |
completed | May 3, 2026, 6:02 a.m. |
Created at: May 1, 2026, 1:37 a.m.