Triple
T650196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red 1 |
E11328
|
entity |
| Predicate | safetyResponsibility |
P636
|
FINISHED |
| Object | overall formation safety |
—
|
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: overall formation safety | Statement: [Red 1, safetyResponsibility, overall formation safety]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyResponsibility Context triple: [Red 1, safetyResponsibility, overall formation safety]
-
A.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
B.
responsibleFor
chosen
Indicates that one entity has a duty, obligation, or role to manage, oversee, or be accountable for another entity or outcome.
-
C.
establishesLiabilityFor
Indicates that one party is held legally responsible or accountable for a particular act, omission, or outcome.
-
D.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
E.
publicSafetyAgencyType
Indicates the specific category or kind of public safety agency associated with an entity (e.g., police, fire, emergency medical services).
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.