Triple
T11698302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CB2 receptor |
E278052
|
entity |
| Predicate | hasTherapeuticPotentialIn |
P39637
|
FINISHED |
| Object | chronic pain |
—
|
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: chronic pain | Statement: [CB2 receptor, hasTherapeuticPotentialIn, chronic pain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTherapeuticPotentialIn Context triple: [CB2 receptor, hasTherapeuticPotentialIn, chronic pain]
-
A.
potentialTherapeuticUse
chosen
Indicates that something is being considered or investigated as a possible treatment or therapy for a condition or disease.
-
B.
hasTherapeuticGoal
Indicates that an action, treatment, or intervention is undertaken with the intention of achieving a specific therapeutic or health-related outcome.
-
C.
hasPharmacologicalEffect
Indicates that one entity produces a specific pharmacological effect or action on another entity.
-
D.
medicinalUse
Indicates that one entity is used as a treatment or remedy for a disease, condition, or health-related purpose affecting another entity.
-
E.
hasTheoreticalTreatment
Indicates that a subject is associated with, or described by, a theoretical explanation, model, or framework addressing it.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47df68c81908a91919a69b4880d |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.