Triple
T35767099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elliott County, Kentucky |
E1034045
|
entity |
| Predicate | hasPredominantLandCover |
P2022
|
FINISHED |
| Object | 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: forest | Statement: [Elliott County, Kentucky, hasPredominantLandCover, forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredominantLandCover Context triple: [Elliott County, Kentucky, hasPredominantLandCover, 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.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
C.
hasLandClassification
Indicates the designated land-use or land-cover category assigned to a particular area or parcel.
-
D.
vegetationCoverage
Indicates the extent or proportion of an area that is covered by vegetation.
-
E.
hasLikelyLandUse
Indicates that an area or parcel is associated with a predicted or most probable type of land use (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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.