Triple
T24018980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheat River basin |
E594763
|
entity |
| Predicate | hasMajorLandcover |
P2022
|
FINISHED |
| Object | mixed hardwood forest |
—
|
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: mixed hardwood forest | Statement: [Cheat River basin, hasMajorLandcover, mixed hardwood forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorLandcover Context triple: [Cheat River basin, hasMajorLandcover, mixed hardwood forest]
-
A.
hasLandCoverage
chosen
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
B.
hasMajorEcoregion
Indicates that an entity is primarily located within, or chiefly associated with, a particular major ecological region.
-
C.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
-
D.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
E.
vegetationCoverage
Indicates the extent or proportion of an area that is covered by vegetation.
- 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_69e288be2c288190a3a46006945557f7 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d5a7b5848190849e7a0f035465b3 |
completed | April 29, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:42 p.m.