Triple
T36463814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tetraodon nigroviridis |
E898370
|
entity |
| Predicate | toxinPresence |
P152892
|
FINISHED |
| Object | may contain tetrodotoxin |
—
|
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: may contain tetrodotoxin | Statement: [Tetraodon nigroviridis, toxinPresence, may contain tetrodotoxin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toxinPresence Context triple: [Tetraodon nigroviridis, toxinPresence, may contain tetrodotoxin]
-
A.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
B.
toxinLocation
Indicates the place or environment where a toxin is present, stored, or exerts its effect.
-
C.
featuresToxin
chosen
Indicates that an entity contains, produces, or is characterized by the presence of a toxin.
-
D.
toxinProduced
Indicates that one entity generates or secretes a substance that is toxic or harmful to another entity or its environment.
-
E.
toxicTo
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
- 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_69f76e58ebd88190b75d9b169b59d793 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.