Triple
T22674764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ADAAA |
E560317
|
entity |
| Predicate | mitigatingMeasuresExcluded |
P149192
|
FINISHED |
| Object | medication |
—
|
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: medication | Statement: [ADAAA, mitigatingMeasuresExcluded, medication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mitigatingMeasuresExcluded Context triple: [ADAAA, mitigatingMeasuresExcluded, medication]
-
A.
requiresMitigation
Indicates that something poses a risk or issue that must be addressed through specific mitigation actions or measures.
-
B.
reasonForSpecialMeasures
Indicates that one entity specifies the justification or cause for which special measures or exceptional actions are taken regarding another entity.
-
C.
builtAsMitigationFor
Indicates that one entity was constructed specifically to reduce, prevent, or counteract a particular risk, problem, or adverse impact associated with another entity.
-
D.
protectionMeasures
Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
-
E.
safeguardingMeasuresInclude
Indicates that certain specific protective or security measures are contained within, or form part of, a broader set of safeguarding measures.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178229e908190b696d14a93c11344 |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:10 p.m.