Triple
T2575554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Organized Crime and Gang Section |
E57765
|
entity |
| Predicate | goal |
P68
|
FINISHED |
| Object | protect communities from organized criminal threats |
—
|
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: protect communities from organized criminal threats | Statement: [Organized Crime and Gang Section, goal, protect communities from organized criminal threats]
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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a43f188190a3d7538bf7867466 |
completed | March 7, 2026, 7:28 a.m. |
Created at: March 6, 2026, 9:49 p.m.