Triple
T8440003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narada Falls |
E199326
|
entity |
| Predicate | longestDrop |
P47584
|
FINISHED |
| Object | approximately 159 feet |
—
|
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: approximately 159 feet | Statement: [Narada Falls, longestDrop, approximately 159 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longestDrop Context triple: [Narada Falls, longestDrop, approximately 159 feet]
-
A.
skiVerticalDrop
Indicates the vertical distance in elevation from the top to the bottom of a ski run or ski area.
-
B.
verticalDrop_ft
Indicates the vertical distance, measured in feet, that one entity drops or falls relative to another reference level.
-
C.
approximateHeightOfFallsViewed
Indicates the estimated vertical height of the waterfalls as observed or perceived by the viewer.
-
D.
waterfallHeight
chosen
Indicates the vertical distance or drop in elevation from the top to the bottom of a waterfall.
-
E.
distanceFallen
Indicates the amount of vertical distance an object has moved downward from its starting point due to falling.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:08 p.m.