Triple
T473404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lupinus |
E9007
|
entity |
| Predicate | hasToxicPart |
P35
|
FINISHED |
| Object | seeds (in high-alkaloid species) |
—
|
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: seeds (in high-alkaloid species) | Statement: [Lupinus, hasToxicPart, seeds (in high-alkaloid species)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToxicPart Context triple: [Lupinus, hasToxicPart, seeds (in high-alkaloid species)]
-
A.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
B.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
C.
hasPart
chosen
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
E.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0208c788190a96cdabcf593fda7 |
completed | Feb. 28, 2026, 1:39 p.m. |
| PD | Predicate disambiguation | batch_69a2edecefb081908331ef8b9edf6636 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.