Triple
T24823242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freyd–Mitchell embedding theorem |
E621113
|
entity |
| Predicate | typicalTargetCategory |
P132779
|
FINISHED |
| Object | category of modules over a ring |
—
|
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: category of modules over a ring | Statement: [Freyd–Mitchell embedding theorem, typicalTargetCategory, category of modules over a ring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTargetCategory Context triple: [Freyd–Mitchell embedding theorem, typicalTargetCategory, category of modules over a ring]
-
A.
typicalTargetType
chosen
Indicates the usual or most common type or category of entity that serves as the target or recipient in a given relationship or action.
-
B.
commonUseCategory
Indicates that multiple entities share the same general category of use or functional purpose.
-
C.
cornerCategory
Indicates that something is classified as belonging to a specific type or category of corner.
-
D.
agingCategory
Indicates the classification of an entity based on its stage or degree of aging.
-
E.
socialCategory
Indicates that an entity belongs to, or is classified within, a particular social group, class, or category.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 18, 2026, 5:05 a.m.