Triple
T7570540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rayleigh waves |
E179226
|
entity |
| Predicate | damagePotential |
P32756
|
FINISHED |
| Object | can cause significant damage to buildings |
—
|
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: can cause significant damage to buildings | Statement: [Rayleigh waves, damagePotential, can cause significant damage to buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damagePotential Context triple: [Rayleigh waves, damagePotential, can cause significant damage to buildings]
-
A.
damageTo
chosen
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
B.
damageAdjusted
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
-
C.
primaryDamageType
Indicates the main kind of harm or injury that an action, event, or object is responsible for causing.
-
D.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
E.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f920540c8190817712db5aa3eeff |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4de77048190b8769e717fdcf8e7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.