Triple
T9175302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tacoma Narrows |
E220183
|
entity |
| Predicate | bridgeCollapseInfluence |
P54339
|
FINISHED |
| Object | advances in bridge aerodynamics |
—
|
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: advances in bridge aerodynamics | Statement: [Tacoma Narrows, bridgeCollapseInfluence, advances in bridge aerodynamics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bridgeCollapseInfluence Context triple: [Tacoma Narrows, bridgeCollapseInfluence, advances in bridge aerodynamics]
-
A.
engineerOfCollapsedBridge
Indicates that the subject is the engineer responsible for designing, constructing, or overseeing the bridge that subsequently collapsed.
-
B.
towerCollapsedIn
Indicates that a tower underwent structural failure and collapsed at or within a specified location or context.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
infrastructureImpact
chosen
Indicates the effect that an action, event, or entity has on the condition, performance, or availability of infrastructure systems.
-
E.
originalBridgeDestroyed
Indicates that the initially existing bridge in a given context has been destroyed.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbfa2f9708190a955bf28a4f04004 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.