Triple
T1160360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elm |
E24476
|
entity |
| Predicate | sideEffectManagement |
P25611
|
FINISHED |
| Object | managed via Elm runtime |
—
|
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: managed via Elm runtime | Statement: [Elm, sideEffectManagement, managed via Elm runtime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sideEffectManagement Context triple: [Elm, sideEffectManagement, managed via Elm runtime]
-
A.
hasCommonSideEffect
Indicates that two or more treatments, drugs, or interventions share at least one side effect in common.
-
B.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
C.
registrationEffect
Indicates the outcome or consequence that results from an entity being registered or from the act of registration taking place.
-
D.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
-
E.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcaf3a9081908bad2eba74dffbc1 |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:45 p.m.