Triple
T30143944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shuibuya Dam |
E766200
|
entity |
| Predicate | spillwayLocation |
P168482
|
FINISHED |
| Object | dam crest |
—
|
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: dam crest | Statement: [Shuibuya Dam, spillwayLocation, dam crest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spillwayLocation Context triple: [Shuibuya Dam, spillwayLocation, dam crest]
-
A.
hasSpillway
Indicates that a dam or similar water-retaining structure is equipped with a spillway for controlled release or overflow of water.
-
B.
spillwayCount
Indicates the number of spillways associated with or present in a given structure or location.
-
C.
waterfallLocation
Indicates the spatial location or geographic area where a waterfall is situated.
-
D.
riverLocation
Indicates that a river is located in, passes through, or is geographically associated with a specified place or region.
-
E.
spurLocation
Indicates the specific place or region where a spur (such as a projection, offshoot, or secondary feature) is situated relative to another entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 7:18 p.m.