Triple
T17619702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodgers Creek Fault |
E429674
|
entity |
| Predicate | hasPotentialImpactOn |
P125238
|
FINISHED |
| Object | San Francisco Bay Area economy |
—
|
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: San Francisco Bay Area economy | Statement: [Rodgers Creek Fault, hasPotentialImpactOn, San Francisco Bay Area economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPotentialImpactOn Context triple: [Rodgers Creek Fault, hasPotentialImpactOn, San Francisco Bay Area economy]
-
A.
canImpact
chosen
Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
-
B.
hasCanonicalImpactOn
Indicates that one entity exerts a standard, authoritative, or officially recognized influence or effect on another entity.
-
C.
hasPossibleInfluence
Indicates that one entity may have an effect on, contribute to, or shape the state, behavior, or outcome of another entity, without asserting that this influence is definite or direct.
-
D.
hasImplicationsFor
Indicates that one entity’s state, action, or condition leads to consequences, effects, or relevance for another entity.
-
E.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d3547d88190ae3c9ffed63133c9 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.