Triple
T15819555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CiMUS |
E383567
|
entity |
| Predicate | focusDiseaseType |
P31647
|
FINISHED |
| Object | chronic diseases |
—
|
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 diseases | Statement: [CiMUS, focusDiseaseType, chronic diseases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusDiseaseType Context triple: [CiMUS, focusDiseaseType, chronic diseases]
-
A.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
B.
focusType
chosen
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
C.
diseaseBurdenType
Indicates the type or category of burden (e.g., mortality, morbidity, economic impact) that a disease imposes.
-
D.
addressesDiseaseType
Indicates that something (such as a treatment, intervention, or action) is directed toward managing, treating, or affecting a specific type of disease.
-
E.
basedOnDisease
Indicates that something (such as a decision, classification, or action) is determined or derived on the basis of a particular disease or disease-related information.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a6e6748190acb0791bd465587f |
completed | April 16, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.