Triple
T10023659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto-Encoding Variational Bayes |
E200670
|
entity |
| Predicate | introducesTechnique |
P3047
|
FINISHED |
| Object | reparameterization trick |
—
|
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: reparameterization trick | Statement: [Auto-Encoding Variational Bayes, introducesTechnique, reparameterization trick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducesTechnique Context triple: [Auto-Encoding Variational Bayes, introducesTechnique, reparameterization trick]
-
A.
hasTechnique
chosen
Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
-
B.
featuresTechnique
Indicates that something incorporates or makes use of a particular technique as part of its content or execution.
-
C.
techniqueRequired
Indicates that performing one entity (such as an action, process, or task) necessitates the use of a specific technique associated with the other entity.
-
D.
allowedTechnique
Indicates that a particular technique or method is permitted or acceptable to use in a given context or under specified rules.
-
E.
artisticTechnique
Indicates the method, style, or process used to create or execute an artistic work.
- 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_69ca831c45f08190ac1505cc15076608 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd7c75548190aa604d90d63dc111 |
completed | April 2, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.