Triple
T19040325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PR3-ANCA |
E465982
|
entity |
| Predicate | antigenType |
P37229
|
FINISHED |
| Object | serine protease |
—
|
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: serine protease | Statement: [PR3-ANCA, antigenType, serine protease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antigenType Context triple: [PR3-ANCA, antigenType, serine protease]
-
A.
antigen
chosen
Indicates that one entity functions as an antigen in relation to another, typically provoking or being recognized by an immune response.
-
B.
antibodyType
Indicates the specific class or subtype of an antibody involved in the described relationship or context.
-
C.
antigensExpressedOn
Indicates that specific antigens are present on the surface of a given cell or biological structure.
-
D.
antigenicSubtype
Indicates a relationship where one entity is classified as a specific antigenic subtype or variant of another based on its antigenic properties.
-
E.
immunityType
Indicates the specific kind or category of immunity that applies in a given context (e.g., legal, diplomatic, medical).
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d80054c88190a9d3a49aed504235 |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4a3001e388190aa6057266514e75a |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.