Triple
T17407124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Post Oak Savannah ecoregion |
E423244
|
entity |
| Predicate | typicalLandCover |
P953
|
FINISHED |
| Object | oak woodland patches |
—
|
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: oak woodland patches | Statement: [Post Oak Savannah ecoregion, typicalLandCover, oak woodland patches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLandCover Context triple: [Post Oak Savannah ecoregion, typicalLandCover, oak woodland patches]
-
A.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
C.
vegetationCoverage
Indicates the extent or proportion of an area that is covered by vegetation.
-
D.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
E.
majorLandUse
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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b081ae08190b144e333a3a74b02 |
completed | April 19, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.