Triple
T22629754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2,4-D |
E558515
|
entity |
| Predicate | hasToxicityProfile |
P133530
|
FINISHED |
| Object | moderate acute toxicity 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: moderate acute toxicity to humans | Statement: [2,4-D, hasToxicityProfile, moderate acute toxicity to humans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToxicityProfile Context triple: [2,4-D, hasToxicityProfile, moderate acute toxicity to humans]
-
A.
toxicityRoute
Indicates the route or pathway through which a toxic effect or substance is delivered or exposed to an entity.
-
B.
toxicityType
chosen
Indicates the specific kind or category of toxic effect associated with a substance, action, or exposure.
-
C.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
D.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
E.
notableToxicity
Indicates that an entity is recognized for having a significant level or history of toxicity, harm, or detrimental effects in its context or interactions.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e3febd081909ff21abef1e4035d |
completed | April 29, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 3:02 p.m.