Triple
T936699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zelkova |
E20211
|
entity |
| Predicate | resistantTo |
P2081
|
FINISHED |
| Object | Dutch elm disease (relative to Ulmus) |
—
|
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: Dutch elm disease (relative to Ulmus) | Statement: [Zelkova, resistantTo, Dutch elm disease (relative to Ulmus)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resistantTo Context triple: [Zelkova, resistantTo, Dutch elm disease (relative to Ulmus)]
-
A.
designedToWithstand
Indicates that something has been intentionally created or engineered to resist, endure, or remain functional under specified conditions, forces, or stresses.
-
B.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
C.
diseaseResistance
chosen
Indicates how effectively one entity can prevent, withstand, or recover from harmful effects caused by a particular disease or pathogen in relation to another.
-
D.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
-
E.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3668a3c8190b0152166efa93ee1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.