Triple
T8556812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coos River |
E202589
|
entity |
| Predicate | hasBasinLandUse |
P38195
|
FINISHED |
| Object | commercial forestry |
—
|
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: commercial forestry | Statement: [Coos River, hasBasinLandUse, commercial forestry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBasinLandUse Context triple: [Coos River, hasBasinLandUse, commercial forestry]
-
A.
hasWatershedUse
Indicates that a particular type of use, activity, or function is associated with or applied to a watershed.
-
B.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
C.
hasFloodplainUse
Indicates that a floodplain area is being used or designated for a particular purpose or activity.
-
D.
basinType
Indicates the specific kind or classification of a basin associated with an entity (e.g., by form, function, or hydrological role).
-
E.
majorLandUse
chosen
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe946d1408190adc7dfb7b2173f9d |
completed | March 31, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69cbd1160fcc8190aa380a73610af731 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.