Triple
T28235411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huanggoushu Waterfall region |
E711865
|
entity |
| Predicate | mainWaterfallHeight |
P47584
|
FINISHED |
| Object | about 77.8 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 77.8 metres | Statement: [Huanggoushu Waterfall region, mainWaterfallHeight, about 77.8 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainWaterfallHeight Context triple: [Huanggoushu Waterfall region, mainWaterfallHeight, about 77.8 metres]
-
A.
waterfallHeight
chosen
Indicates the vertical distance or drop in elevation from the top to the bottom of a waterfall.
-
B.
majorWaterfall
Indicates that a waterfall is of significant size, height, or volume relative to other waterfalls.
-
C.
numberOfMajorWaterfallsInCity
Indicates the count of major waterfalls located within a given city.
-
D.
primaryWaterfall
Indicates that one entity serves as the main or most significant waterfall associated with another entity.
-
E.
waterfallName
Indicates that an entity is identified by or associated with the specific name of 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_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:54 p.m.