Triple
T15739930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nandina |
E381573
|
entity |
| Predicate | toxicityToAnimals |
P6478
|
FINISHED |
| Object | toxic to some birds |
—
|
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: toxic to some birds | Statement: [Nandina, toxicityToAnimals, toxic to some birds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toxicityToAnimals Context triple: [Nandina, toxicityToAnimals, toxic to some birds]
-
A.
toxicTo
chosen
Indicates that one entity causes harm, poisoning, or adverse effects to another when exposed or applied.
-
B.
toxicityRoute
Indicates the route or pathway through which a toxic effect or substance is delivered or exposed to an entity.
-
C.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
D.
usesAnimalCarcass
Indicates that an entity makes use of an animal’s dead body or its remains for some purpose.
-
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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.