Triple
T33316225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Health Research |
E853023
|
entity |
| Predicate | supportsStudyType |
P200184
|
FINISHED |
| Object | observational studies |
—
|
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: observational studies | Statement: [Apple Health Research, supportsStudyType, observational studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsStudyType Context triple: [Apple Health Research, supportsStudyType, observational studies]
-
A.
supportsLevelOfStudy
Indicates that one entity provides or is compatible with a specified level of academic or educational study for another entity.
-
B.
hasStudyType
chosen
Indicates that an entity is associated with or characterized by a particular type or design of study.
-
C.
canBeStudiedAs
Indicates that something is suitable or appropriate to be examined, analyzed, or researched as a subject of study.
-
D.
studType
Indicates a relationship where an entity is classified as a particular type or category of stud (e.g., a specific kind of fastener or structural element).
-
E.
supportsDisciplineType
Indicates that one entity provides backing, resources, or compatibility for a specified type of discipline (e.g., academic, professional, or technical field).
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:33 a.m.