Triple
T20076866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuyuna Range |
E499889
|
entity |
| Predicate | reclamationUse |
P138609
|
FINISHED |
| Object | recreation area |
—
|
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: recreation area | Statement: [Cuyuna Range, reclamationUse, recreation area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reclamationUse Context triple: [Cuyuna Range, reclamationUse, recreation area]
-
A.
reservoirUse
Indicates the way a reservoir is utilized or the purpose for which its stored water is used.
-
B.
hasLandReclamation
Indicates that an entity has carried out, is involved in, or is characterized by the process of creating new land from oceans, rivers, or other water bodies.
-
C.
basinUse
Indicates that a basin is used for a particular purpose, activity, or function.
-
D.
hasRiverUse
Indicates that one entity makes use of a river associated with another entity, such as for transport, irrigation, recreation, or other purposes.
-
E.
hasWatershedUse
Indicates that a particular type of use, activity, or function is associated with or applied to a watershed.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643bcfd48190893abd3734f15cd3 |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:40 p.m.