Triple
T7400147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silesian Beskids |
E170725
|
entity |
| Predicate | hasForestCover |
P71211
|
FINISHED |
| Object | predominantly forested |
—
|
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: predominantly forested | Statement: [Silesian Beskids, hasForestCover, predominantly forested]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForestCover Context triple: [Silesian Beskids, hasForestCover, predominantly forested]
-
A.
hasForestType
Indicates that an area or location is characterized by a specific type or classification of forest.
-
B.
isForested
chosen
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
C.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
D.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
E.
hasMajorForest
Indicates that an entity possesses or contains a large, significant forested area.
- 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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f24dbf288190b8dfea455148841b |
completed | March 27, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:10 p.m.