Triple
T12469271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Welsh uplands |
E298009
|
entity |
| Predicate | influenceOnRivers |
P105164
|
FINISHED |
| Object | source area for fast-flowing upland streams |
—
|
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: source area for fast-flowing upland streams | Statement: [Welsh uplands, influenceOnRivers, source area for fast-flowing upland streams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influenceOnRivers Context triple: [Welsh uplands, influenceOnRivers, source area for fast-flowing upland streams]
-
A.
drainageInfluencedBy
Indicates that the pattern, direction, or effectiveness of drainage is affected or controlled by another factor or entity.
-
B.
impactedRiver
Indicates that one entity has caused a significant effect, alteration, or disturbance to a river or its conditions.
-
C.
associatedRiverBasin
Indicates that one entity is linked to, or lies within the drainage area of, a particular river basin.
-
D.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
E.
operatesOnRiver
Indicates that an entity conducts its operations or activities on, along, or directly involving a river.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e5f8d04819086d1ad4d62364005 |
completed | April 10, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.