Triple
T10502848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FreeStyle Libre |
E247712
|
entity |
| Predicate | readerDisplay |
P23135
|
FINISHED |
| Object | current glucose value |
—
|
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: current glucose value | Statement: [FreeStyle Libre, readerDisplay, current glucose value]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readerDisplay Context triple: [FreeStyle Libre, readerDisplay, current glucose value]
-
A.
readingSystem
Indicates a system or device that presents, interprets, or processes written or digital content for a user.
-
B.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
-
C.
readout
chosen
Indicates that one entity reports, displays, or outputs the measured or computed value of another entity.
-
D.
readingAid
Indicates that one entity assists or facilitates another entity’s ability to read or engage in reading activities.
-
E.
readingTechnology
Indicates a relationship where a reading activity involves or is carried out using a particular technology.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099c6a848190bf1d5361e9e61108 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8e24ac8190912c9f11b8bd3084 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:25 p.m.