Triple
T25855220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Davidson summit area |
E651323
|
entity |
| Predicate | oftenAffectedBy |
P25489
|
FINISHED |
| Object | coastal fog |
—
|
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: coastal fog | Statement: [Mount Davidson summit area, oftenAffectedBy, coastal fog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenAffectedBy Context triple: [Mount Davidson summit area, oftenAffectedBy, coastal fog]
-
A.
areAffectedBy
chosen
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
B.
alsoAffects
Indicates that an action, condition, or change impacting one entity additionally impacts another entity as well.
-
C.
affectsRelationshipBetween
Indicates that one entity causes a change or influence on the nature, quality, or status of the relationship between two or more other entities.
-
D.
standAffected
Indicates that an entity is in a state or position of being impacted or influenced by another entity or event.
-
E.
affectedPerson
Indicates that a particular person is impacted or influenced by an event, action, or condition.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 22, 2026, 8 a.m.