Triple
T4260417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ephedra |
E96088
|
entity |
| Predicate | isToxic |
P54183
|
FINISHED |
| Object | can be toxic at high doses |
—
|
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: can be toxic at high doses | Statement: [Ephedra, isToxic, can be toxic at high doses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isToxic Context triple: [Ephedra, isToxic, can be toxic at high doses]
-
A.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
B.
toxicPart
Indicates that one entity is a component or portion of another that is harmful, poisonous, or otherwise toxic.
-
C.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
D.
notableToxicity
chosen
Indicates that an entity is recognized for having a significant level or history of toxicity, harm, or detrimental effects in its context or interactions.
-
E.
toxinEffect
Indicates the harmful impact or physiological response caused by a toxin on a target 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f8103b48190934a810faafa6cb7 |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.