Triple
T12959303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Jack Griffin |
E310095
|
entity |
| Predicate | drugName |
P69332
|
FINISHED |
| Object | monocaine |
—
|
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: monocaine | Statement: [Dr. Jack Griffin, drugName, monocaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drugName Context triple: [Dr. Jack Griffin, drugName, monocaine]
-
A.
drugGenericName
Indicates that a drug entity is associated with its generic (non-brand) name.
-
B.
drugProduced
Indicates that a particular drug is manufactured or generated by a specified producer or source.
-
C.
drugClass
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
D.
hasDrug
chosen
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
E.
evaluatedDrug
Indicates that a particular drug has been assessed or tested, typically in the context of a study, experiment, or evaluation process.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.