Triple
T34458929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kegon Falls |
E884579
|
entity |
| Predicate | secondaryFallsDescription |
P198929
|
FINISHED |
| Object | numerous smaller cascades along surrounding cliffs |
—
|
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: numerous smaller cascades along surrounding cliffs | Statement: [Kegon Falls, secondaryFallsDescription, numerous smaller cascades along surrounding cliffs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryFallsDescription Context triple: [Kegon Falls, secondaryFallsDescription, numerous smaller cascades along surrounding cliffs]
-
A.
secondAccidentType
Indicates the type or category of a second (subsequent) accident associated with an entity or event.
-
B.
resultOfFall
Indicates that something exists or occurs as a consequence or outcome of a fall event.
-
C.
fallsFrom
Indicates that one entity moves downward or drops starting from the location or position of another entity.
-
D.
fallsWith
Indicates that one entity falls at the same time as, or as a consequence of, another entity falling.
-
E.
secondaryFire
Indicates the use or activation of an alternate or secondary mode of firing in a weapon or tool, distinct from its primary fire action.
- F. None of above. chosen
Provenance (4 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
| PDg | Predicate description generation | batch_69ff14d4dfc48190bc9fba2384988a98 |
completed | May 9, 2026, 11:04 a.m. |
Created at: May 1, 2026, 2 a.m.