Triple
T25464555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Climate Scoping Plan |
E638138
|
entity |
| Predicate | aimsTo |
P79
|
FINISHED |
| Object | improve public health through reduced pollution |
—
|
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: improve public health through reduced pollution | Statement: [California Climate Scoping Plan, aimsTo, improve public health through reduced pollution]
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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f72f1a788190904ed62ebdccc57c |
completed | May 2, 2026, 1:07 p.m. |
Created at: April 21, 2026, 2:14 p.m.