Triple
T19313062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chili Bar run |
E483019
|
entity |
| Predicate | hasRiverSectionType |
P116240
|
FINISHED |
| Object | whitewater |
—
|
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: whitewater | Statement: [Chili Bar run, hasRiverSectionType, whitewater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverSectionType Context triple: [Chili Bar run, hasRiverSectionType, whitewater]
-
A.
includesHydrologicalSection
chosen
Indicates that one entity contains or encompasses a specific hydrological section as part of its spatial or structural extent.
-
B.
hasRiverBedType
Indicates the type or classification of the riverbed associated with a given river or watercourse.
-
C.
hasRiverCode
Indicates that a river is associated with a specific identifying code or classification value.
-
D.
hasTributaryType
Indicates that one watercourse is classified as a specific type of tributary in relation to another water body.
-
E.
hasRiverineCharacteristic
Indicates that something possesses qualities, features, or conditions associated with rivers or river environments.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cf25c081908a30814b15d78c25 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.