Triple
T22187685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyophysitism |
E548337
|
entity |
| Predicate | teachesUnionType |
P13197
|
FINISHED |
| Object | union in one person |
—
|
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: union in one person | Statement: [Dyophysitism, teachesUnionType, union in one person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesUnionType Context triple: [Dyophysitism, teachesUnionType, union in one person]
-
A.
typeOfUnion
Indicates the specific kind or category of union relationship that exists between the related entities.
-
B.
hasTeacherType
Indicates that an entity is associated with a teacher characterized by a specific type or category (e.g., role, specialization, or employment status).
-
C.
unificationType
Indicates the specific manner or category in which two or more entities are combined, merged, or treated as a single unified whole.
-
D.
isTaughtAs
chosen
Indicates that something is presented or delivered as instructional content, typically within an educational or training context.
-
E.
representsUnion
Indicates that one entity functions as a union or collective body that formally represents the interests or rights of another entity or group.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aaa32288190830f6dfc626fb26a |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.