Triple
T2190441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tylenol |
E49847
|
entity |
| Predicate | shouldBeUsedWithCautionIn |
P2399
|
FINISHED |
| Object | patients with liver disease |
—
|
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: patients with liver disease | Statement: [Tylenol, shouldBeUsedWithCautionIn, patients with liver disease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shouldBeUsedWithCautionIn Context triple: [Tylenol, shouldBeUsedWithCautionIn, patients with liver disease]
-
A.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
B.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
C.
restrictedFromUseFor
Indicates that something is prohibited or limited from being used for a specified purpose, context, or application.
-
D.
recommendsUseOf
Indicates that one entity advises, endorses, or suggests the use of another entity as appropriate or beneficial in a given context.
-
E.
warnsAbout
chosen
Indicates that one entity alerts or cautions another entity about a potential danger, risk, or problem.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf9e99f08190892d34485c8f2f25 |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda32d1881909d1fd83a751fb21c |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.