Triple
T3859269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tay Bridge disaster |
E90093
|
entity |
| Predicate | impactOnField |
P52396
|
FINISHED |
| Object | bridge engineering |
—
|
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: bridge engineering | Statement: [Tay Bridge disaster, impactOnField, bridge engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnField Context triple: [Tay Bridge disaster, impactOnField, bridge engineering]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
seasonImpact
Indicates how a particular season influences or affects another entity, condition, or outcome.
-
C.
impactOnPerformance
Indicates that one entity has an effect, influence, or consequence on the performance level or effectiveness of another entity.
-
D.
impactOnStandings
Indicates how an event or outcome affects the relative rankings or standings within a competition or system.
-
E.
impactOnLeader
Indicates that one entity has an effect, influence, or consequence on a leader within a given context.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1ff39c8190b83a88abd840a0e3 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aeeb828fb08190901d51edbe8bd304 |
completed | March 9, 2026, 3:47 p.m. |
Created at: March 9, 2026, 3:19 p.m.