Triple
T1106310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anacardiaceae |
E25494
|
entity |
| Predicate | containsAllergenicCompound |
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: [Anacardiaceae, containsAllergenicCompound, urushiol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAllergenicCompound Context triple: [Anacardiaceae, containsAllergenicCompound, urushiol]
-
A.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
B.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
C.
hasNotableDrug
Indicates that an entity is associated with a drug that is considered notable or significant in some recognized context.
-
D.
hasComb
Indicates that an entity possesses or is equipped with a comb.
-
E.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9e339f88190afc027216e95d2f7 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b74877748190b78cd8847ee4fa7a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:43 p.m.