Triple
T50234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch elm disease |
E987
|
entity |
| Predicate | affectsOrgan |
P1586
|
FINISHED |
| Object | xylem |
—
|
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: xylem | Statement: [Dutch elm disease, affectsOrgan, xylem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsOrgan Context triple: [Dutch elm disease, affectsOrgan, xylem]
-
A.
hasMainOrgan
Indicates that an entity possesses a primary or principal organ that plays a central role in its biological or functional system.
-
B.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
C.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
D.
affectsOffice
Indicates that one entity has an influence or impact on the condition, function, or status of an office.
-
E.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
- 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_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. |
Created at: Feb. 28, 2026, 1:47 a.m.