Triple
T37584643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinkhole Capital of the United States |
E935063
|
entity |
| Predicate | impliesRisk |
P103131
|
FINISHED |
| Object | ground subsidence potential |
—
|
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: ground subsidence potential | Statement: [Sinkhole Capital of the United States, impliesRisk, ground subsidence potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impliesRisk Context triple: [Sinkhole Capital of the United States, impliesRisk, ground subsidence potential]
-
A.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
C.
riskTakenFor
Indicates that one entity accepts or undertakes a risk for the benefit, protection, or sake of another entity.
-
D.
safetyImplication
chosen
Indicates that one entity has a consequence, effect, or relevance for the safety or risk level associated with another entity or situation.
-
E.
riskIncreasedBy
Indicates that the level or likelihood of risk is raised or made greater as a result of the influencing entity or factor.
- 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:17 p.m.