Triple
T2320028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shortgrass prairie |
E51158
|
entity |
| Predicate | hasDominantVegetationType |
P953
|
FINISHED |
| Object | short grasses |
—
|
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: short grasses | Statement: [Shortgrass prairie, hasDominantVegetationType, short grasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDominantVegetationType Context triple: [Shortgrass prairie, hasDominantVegetationType, short grasses]
-
A.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
B.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
C.
hasCanopyDensity
Indicates the degree to which a canopy (such as a tree or forest cover) occupies or obscures the area beneath it.
-
D.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
-
E.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.