Triple
T31535547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benserazide |
E804591
|
entity |
| Predicate | reducesAdverseEffect |
P9925
|
FINISHED |
| Object | nausea |
—
|
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: nausea | Statement: [Benserazide, reducesAdverseEffect, nausea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reducesAdverseEffect Context triple: [Benserazide, reducesAdverseEffect, nausea]
-
A.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
-
B.
reduces
chosen
Indicates that one entity causes a decrease in the amount, intensity, degree, or impact of another entity.
-
C.
opposesEffectOf
Indicates that one entity counteracts, reduces, or nullifies the effect produced by another entity.
-
D.
commonAdverseReactions
Indicates that the related entities are linked through adverse reactions or side effects that frequently occur in association with one another.
-
E.
possibleSideEffect
Indicates that one entity may occur as a side effect or unintended consequence of another entity or action.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 10:03 p.m.