Triple
T50215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulmus |
E986
|
entity |
| Predicate | vectorOfDutchElmDisease |
P2893
|
FINISHED |
| Object | elm bark beetles |
—
|
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: elm bark beetles | Statement: [Ulmus, vectorOfDutchElmDisease, elm bark beetles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vectorOfDutchElmDisease Context triple: [Ulmus, vectorOfDutchElmDisease, elm bark beetles]
-
A.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
B.
diseaseResistance
Indicates how effectively one entity can prevent, withstand, or recover from harmful effects caused by a particular disease or pathogen in relation to another.
-
C.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
D.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- F. None of above. chosen
Provenance (4 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac23f04819080cef9365ed990d4 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.