Triple
T12013044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridal Veil Falls |
E285952
|
entity |
| Predicate | numberOfMainWaterfallsInNiagaraFalls |
P44271
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Bridal Veil Falls, numberOfMainWaterfallsInNiagaraFalls, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainWaterfallsInNiagaraFalls Context triple: [Bridal Veil Falls, numberOfMainWaterfallsInNiagaraFalls, 3]
-
A.
numberOfMajorWaterfallsOfNiagaraFalls
chosen
Indicates the count of major waterfalls that collectively make up Niagara Falls.
-
B.
hasNumberOfWaterfalls
Indicates the quantity of waterfalls associated with a given entity.
-
C.
majorWaterfall
Indicates that a waterfall is of significant size, height, or volume relative to other waterfalls.
-
D.
primaryWaterfall
Indicates that one entity serves as the main or most significant waterfall associated with another entity.
-
E.
upperFallsHeight
Indicates the vertical height measurement of the upper falls section in a waterfall or multi-tiered cascade.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d884488190b4450a98088208ef |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.