Triple
T16847391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gisborne Airport |
E409578
|
entity |
| Predicate | safetyCoordinationWith |
P435
|
FINISHED |
| Object | railway operations |
—
|
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: railway operations | Statement: [Gisborne Airport, safetyCoordinationWith, railway operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCoordinationWith Context triple: [Gisborne Airport, safetyCoordinationWith, railway operations]
-
A.
safetyContext
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
-
B.
coordinatedWith
chosen
Indicates that two or more entities have worked together in an organized, cooperative manner toward a shared task, goal, or activity.
-
C.
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.
-
D.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related situation.
-
E.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b376bac48190ae09f29a28c55f8c |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.