Triple
T22693619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teglutik |
E561110
|
entity |
| Predicate | overdoseEffect |
P76077
|
FINISHED |
| Object | may cause acute toxicity including neurologic symptoms |
—
|
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 cause acute toxicity including neurologic symptoms | Statement: [Teglutik, overdoseEffect, may cause acute toxicity including neurologic symptoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overdoseEffect Context triple: [Teglutik, overdoseEffect, may cause acute toxicity including neurologic symptoms]
-
A.
hasOverdose
Indicates that an entity has experienced or been involved in an overdose event, typically involving excessive consumption of a substance.
-
B.
riskOfOverdose
chosen
Indicates a likelihood or potential that the subject will experience a drug or substance overdose, given certain conditions or factors.
-
C.
effectOfDeath
Indicates the causal impact or consequences that a death has on another entity, state, or process.
-
D.
toxinEffect
Indicates the harmful impact or physiological response caused by a toxin on a target 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789c6ae481908975b7d27e7624ac |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.