Triple
T30284096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monti Sibillini National Park |
E770182
|
entity |
| Predicate | hasFloraFeature |
P68098
|
FINISHED |
| Object | wildflower meadows |
—
|
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: wildflower meadows | Statement: [Monti Sibillini National Park, hasFloraFeature, wildflower meadows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloraFeature Context triple: [Monti Sibillini National Park, hasFloraFeature, wildflower meadows]
-
A.
hasFloraGroup
chosen
Indicates that an entity is associated with, contains, or is characterized by a particular group or category of plant life.
-
B.
hasFloralFeature
Indicates that an entity possesses a specific floral characteristic, structure, or attribute.
-
C.
hasBiodiversityFeature
Indicates that an entity possesses or is associated with a specific biodiversity-related characteristic, attribute, or element.
-
D.
hasFloralRegion
Indicates that one entity possesses or is associated with a specific floral region as a characteristic or component.
-
E.
FloraDayFeature
Indicates a characteristic or attribute that is specifically associated with a particular day in relation to flora (plants or plant-related events).
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 7:45 p.m.