Triple
T34458928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kegon Falls |
E884579
|
entity |
| Predicate | hasSecondaryFalls |
P90082
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kegon Falls, hasSecondaryFalls, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryFalls Context triple: [Kegon Falls, hasSecondaryFalls, yes]
-
A.
secondaryFallsDescription
Indicates a textual description of additional or secondary waterfalls associated with a primary waterfall or falls feature.
-
B.
hasSecondary
chosen
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
C.
hasTrailBehindFalls
Indicates that a waterfall has a trail or path that passes behind or underneath the falling water.
-
D.
hasSecondarySee
Indicates that an entity has an additional, secondary “see also” reference or cross-link to another related entity.
-
E.
numberOfMajorFalls
Indicates the count of significant or serious falling incidents experienced by an entity within a specified period or context.
- 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffcb5536d88190bfc2e00b854cacfb |
completed | May 10, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69ffc900c2a081909dea04aa60566923 |
completed | May 9, 2026, 11:53 p.m. |
Created at: May 1, 2026, 2 a.m.