Triple
T2869625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American side of Niagara Falls |
E63526
|
entity |
| Predicate | hasApproximateFlowRate |
P5503
|
FINISHED |
| Object | part of total Niagara Falls flow of over 2,400 m³/s |
—
|
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: part of total Niagara Falls flow of over 2,400 m³/s | Statement: [American side of Niagara Falls, hasApproximateFlowRate, part of total Niagara Falls flow of over 2,400 m³/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateFlowRate Context triple: [American side of Niagara Falls, hasApproximateFlowRate, part of total Niagara Falls flow of over 2,400 m³/s]
-
A.
hasFlowRegime
Indicates that one entity is characterized by, or operates under, a particular pattern or regime of flow.
-
B.
waterFlowRate
chosen
Indicates the rate at which water moves or is transported through a given point or system over time.
-
C.
flowsAt
Indicates that a fluid or substance moves through or along a specific location, point, or region.
-
D.
dataRateGeneration
Indicates the rate at which data is produced or generated over time in a given context.
-
E.
dataRate
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfe15ff081908dd1dad62c292b2b |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.