Triple
T12120156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amagasaki derailment |
E288671
|
entity |
| Predicate | impactDescription |
P103390
|
FINISHED |
| Object | train left tracks and crashed into residential building |
—
|
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: train left tracks and crashed into residential building | Statement: [Amagasaki derailment, impactDescription, train left tracks and crashed into residential building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactDescription Context triple: [Amagasaki derailment, impactDescription, train left tracks and crashed into residential building]
-
A.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
B.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
C.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
impactIfCompleted
Indicates the effect or consequence that will occur if the referenced task or action is fully completed.
- F. None of above. chosen
Provenance (4 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916481a008190ae66677b9e6dd961 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:49 p.m.