Triple
T5971924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toxicodendron vernix |
E132892
|
entity |
| Predicate | allergenicComponent |
P23191
|
FINISHED |
| Object | urushiol |
—
|
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: urushiol | Statement: [Toxicodendron vernix, allergenicComponent, urushiol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allergenicComponent Context triple: [Toxicodendron vernix, allergenicComponent, urushiol]
-
A.
containsAllergenicCompound
chosen
Indicates that the subject entity includes one or more compounds known to cause allergic reactions.
-
B.
notableAllergenicGenera
Indicates that the subject is associated with genera that are particularly notable for causing allergic reactions.
-
C.
glutenFreeComponent
Indicates that one entity is a component or ingredient of another and is free from gluten.
-
D.
pollenAllergenicity
Indicates that one entity (typically a type of pollen) has the property or capacity to cause allergic reactions in another entity (such as a person or organism).
-
E.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:03 p.m.