Triple
T8264040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compliance Program Guidance |
E193258
|
entity |
| Predicate | recommends |
P488
|
FINISHED |
| Object | effective lines of communication for reporting compliance concerns |
—
|
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: effective lines of communication for reporting compliance concerns | Statement: [Compliance Program Guidance, recommends, effective lines of communication for reporting compliance concerns]
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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb793aa8f08190b20b3616ceb9bec7 |
completed | March 31, 2026, 7:35 a.m. |
Created at: March 30, 2026, 5:49 p.m.