Triple
T5971927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toxicodendron vernix |
E132892
|
entity |
| Predicate | smokeInhalationFrom |
P39895
|
FINISHED |
| Object | burning plant can cause respiratory irritation |
—
|
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: burning plant can cause respiratory irritation | Statement: [Toxicodendron vernix, smokeInhalationFrom, burning plant can cause respiratory irritation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: smokeInhalationFrom Context triple: [Toxicodendron vernix, smokeInhalationFrom, burning plant can cause respiratory irritation]
-
A.
isInhaled
chosen
Indicates that one entity is taken into another entity through breathing or suction into an internal space such as lungs or airways.
-
B.
smokeSystem
Indicates that an entity is equipped with or associated with a smoke-generating system (e.g., for signaling, testing, or special effects).
-
C.
smokedOver
Indicates that one entity smoked (used tobacco or similar substances) for a duration exceeding a specified time or threshold.
-
D.
smokingMaterial
Indicates that one entity is a material or substance used for smoking by another entity.
-
E.
canBeSmoked
Indicates that something is suitable or able to be consumed by smoking.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc2243c8190bd3488e7b24af985 |
completed | March 22, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c049dcb3c081908ccc9b4d4b210229 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:03 p.m.