Triple
T28235412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huanggoushu Waterfall region |
E711865
|
entity |
| Predicate | mainWaterfallWidth |
P128952
|
FINISHED |
| Object | about 101 metres |
—
|
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: about 101 metres | Statement: [Huanggoushu Waterfall region, mainWaterfallWidth, about 101 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainWaterfallWidth Context triple: [Huanggoushu Waterfall region, mainWaterfallWidth, about 101 metres]
-
A.
waterfallWidthApproximate
chosen
Indicates that the width of a waterfall is approximately a specified value, allowing for some margin of error rather than an exact measurement.
-
B.
waterfallHeight
Indicates the vertical distance or drop in elevation from the top to the bottom of a waterfall.
-
C.
waterfallFlow
Indicates that water moves continuously downward over a vertical or steep drop, forming a waterfall-like flow between locations or surfaces.
-
D.
hasWaterfall
Indicates that one entity possesses, contains, or features a waterfall associated with it.
-
E.
waterfallDrop
Indicates a vertical or near-vertical descent of water from a higher level to a lower level, as in a waterfall.
- 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_69efb51ece308190b8c269a057e36652 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6438d93bc8190bc6788e4852468f8 |
completed | May 2, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:54 p.m.