Triple
T4161953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solanaceae |
E91550
|
entity |
| Predicate | notableToxicity |
P54183
|
FINISHED |
| Object | many species poisonous to humans |
—
|
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: many species poisonous to humans | Statement: [Solanaceae, notableToxicity, many species poisonous to humans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableToxicity Context triple: [Solanaceae, notableToxicity, many species poisonous to humans]
-
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.
notableSafety
Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
-
D.
toxicPart
Indicates that one entity is a component or portion of another that is harmful, poisonous, or otherwise toxic.
-
E.
notableSubstanceReleased
Indicates that an entity has released or emitted a particular notable substance.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0320775c8190b90d80f512060f1c |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:44 p.m.