Triple
T25314420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhine Falls |
E634695
|
entity |
| Predicate | winterFlowRate |
P158378
|
FINISHED |
| Object | about 250 cubic metres per second |
—
|
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 250 cubic metres per second | Statement: [Rhine Falls, winterFlowRate, about 250 cubic metres per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterFlowRate Context triple: [Rhine Falls, winterFlowRate, about 250 cubic metres per second]
-
A.
seasonalFlow
Indicates that the flow or intensity of something varies in a recurring pattern according to the seasons.
-
B.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
C.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
D.
winterSession
Indicates that an event, course, or activity takes place during a designated winter academic or seasonal session.
-
E.
winterCharacteristic
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
- 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_69e75a9847c08190bb02990d06d5ffb7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f49686fcf081908e2ce81665f1c5ea |
completed | May 1, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:27 p.m.