Triple
T12207459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasserstein GAN |
E290870
|
entity |
| Predicate | trainingProcedure |
P16019
|
FINISHED |
| Object | alternates critic and generator updates |
—
|
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: alternates critic and generator updates | Statement: [Wasserstein GAN, trainingProcedure, alternates critic and generator updates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingProcedure Context triple: [Wasserstein GAN, trainingProcedure, alternates critic and generator updates]
-
A.
trainingMethod
chosen
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
B.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
-
C.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
D.
trainingComponent
Indicates that one entity functions as a training-related part, module, or element within a larger training process or system involving another entity.
-
E.
trainingPath
Indicates the sequence or structure of learning or training steps that guide an entity’s progression from a starting level to a targeted skill or competency.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.