Triple
T30143937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuibuya Dam |
E766200
|
entity |
| Predicate | damHeightCategory |
P15960
|
FINISHED |
| Object | one of the tallest concrete-face rock-fill dams in the world |
—
|
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: one of the tallest concrete-face rock-fill dams in the world | Statement: [Shuibuya Dam, damHeightCategory, one of the tallest concrete-face rock-fill dams in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damHeightCategory Context triple: [Shuibuya Dam, damHeightCategory, one of the tallest concrete-face rock-fill dams in the world]
-
A.
damHeight
Indicates the vertical height of a dam structure, typically measured from its base or foundation to its crest.
-
B.
waterfallHeight
Indicates the vertical distance or drop in elevation from the top to the bottom of a waterfall.
-
C.
damCrestElevation
Indicates the height of the top (crest) of a dam above a specified reference level, typically sea level.
-
D.
hasWaterDepthCategory
Indicates the classification of something based on the range or category of its water depth.
-
E.
typeOfDam
chosen
Indicates the specific kind or classification of a dam associated with an entity.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67e8a5c908190abdb6c5aadbaee82 |
completed | May 2, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:18 p.m.