Triple
T10527074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewy body dementia |
E248332
|
entity |
| Predicate | hasTreatmentConsideration |
P94382
|
FINISHED |
| Object | avoid typical antipsychotics when possible |
—
|
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: avoid typical antipsychotics when possible | Statement: [Lewy body dementia, hasTreatmentConsideration, avoid typical antipsychotics when possible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTreatmentConsideration Context triple: [Lewy body dementia, hasTreatmentConsideration, avoid typical antipsychotics when possible]
-
A.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
B.
usesTreatment
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
-
C.
hasSubsequentTreatment
Indicates that one treatment occurs after and in continuation of another treatment in a temporal sequence.
-
D.
subsequentTreatment
Indicates that one treatment occurs after and in response to a prior treatment or medical event.
-
E.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
- F. None of above. chosen
Provenance (4 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f5ec348190875c8c877e70ba4a |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe06d4a48190b1a45dd1d4e16df0 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:29 p.m.