Triple
T20153297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Combat |
E491490
|
entity |
| Predicate | riskForContributors |
P127159
|
FINISHED |
| Object | arrest |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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: arrest | Statement: [Combat, riskForContributors, arrest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskForContributors Context triple: [Combat, riskForContributors, arrest]
-
A.
riskListedBy
Indicates that a risk has been documented, identified, or cataloged by a particular agent or source.
-
B.
riskAddressed
Indicates that a particular risk has been identified and is being mitigated, managed, or otherwise handled by an associated action, control, or measure.
-
C.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
D.
riskToUser
chosen
Indicates that something poses a potential danger, harm, or adverse impact to the user.
-
E.
riskReductionFor
Indicates a relationship where one entity decreases or mitigates the level of risk associated with another entity or situation.
- F. None of above.
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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667dda9b4819097ff66bb2b50fc21 |
completed | April 20, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:34 p.m.