Triple
T22601337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wapama Falls |
E574826
|
entity |
| Predicate | hasViewingStructure |
P127904
|
FINISHED |
| Object | footbridges at base of falls |
—
|
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: footbridges at base of falls | Statement: [Wapama Falls, hasViewingStructure, footbridges at base of falls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewingStructure Context triple: [Wapama Falls, hasViewingStructure, footbridges at base of falls]
-
A.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
B.
hasParticularView
Indicates that one entity holds, expresses, or is characterized by a specific opinion, perspective, or standpoint regarding something.
-
C.
hasViewingPointFor
chosen
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
D.
hasViewThrough
Indicates that one entity can be seen or visually perceived through another entity acting as an intermediate medium or opening.
-
E.
hasViewingAngles
Indicates that one entity possesses or is characterized by specific viewing angles relative to another entity or reference frame.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626db69481908ec9f9c7d320d3cb |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:50 p.m.