Triple
T875599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SNOMED CT |
E18910
|
entity |
| Predicate | codingSystemType |
P20982
|
FINISHED |
| Object | concept identifier based |
—
|
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: concept identifier based | Statement: [SNOMED CT, codingSystemType, concept identifier based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codingSystemType Context triple: [SNOMED CT, codingSystemType, concept identifier based]
-
A.
codingSystemContext
Indicates the coding system or classification framework within which a given code, identifier, or value is defined and interpreted.
-
B.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
C.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
D.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
E.
writingSystemFeatures
Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acae12948190923d31966c26a130 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab9634948190b25ea1b2e34df87d |
completed | March 1, 2026, 9:11 p.m. |
Created at: March 1, 2026, 7:39 p.m.