Triple
T50262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch elm disease |
E987
|
entity |
| Predicate | pathogenType |
P2897
|
FINISHED |
| Object | ascomycete fungus |
—
|
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: ascomycete fungus | Statement: [Dutch elm disease, pathogenType, ascomycete fungus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathogenType Context triple: [Dutch elm disease, pathogenType, ascomycete fungus]
-
A.
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.
-
B.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
C.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
D.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
E.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
- 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.