Triple
T10023651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto-Encoding Variational Bayes |
E200670
|
entity |
| Predicate | introducedAbbreviation |
P12874
|
FINISHED |
| Object | VAE |
E40250
|
NE FINISHED |
How this triple was built (3 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: VAE | Statement: [Auto-Encoding Variational Bayes, introducedAbbreviation, VAE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VAE Context triple: [Auto-Encoding Variational Bayes, introducedAbbreviation, VAE]
-
A.
VQ-VAE
VQ-VAE is a neural network model that combines vector quantization with variational autoencoders to learn discrete latent representations for tasks like image and audio generation.
-
B.
variational autoencoders
chosen
Variational autoencoders are a class of generative neural networks that learn probabilistic latent representations of data, enabling them to generate new, similar samples.
-
C.
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes is the foundational 2013 paper by Kingma and Welling that introduced variational autoencoders, a generative model framework combining deep learning with variational Bayesian inference.
-
D.
VAB
VAB is the commonly used abbreviation for NASA’s Vehicle Assembly Building, the massive structure at Kennedy Space Center where rockets are assembled before launch.
-
E.
VAAU
VAAU is the ICAO airport code for Aurangabad Airport in Maharashtra, India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedAbbreviation Context triple: [Auto-Encoding Variational Bayes, introducedAbbreviation, VAE]
-
A.
establishesAbbreviation
chosen
Indicates that one entity defines or introduces an abbreviated form that stands for another entity.
-
B.
usesAbbreviationIn
Indicates that an entity is referred to by an abbreviated form within a specified context, source, or representation.
-
C.
previousAbbreviation
Indicates that one abbreviation was used earlier or previously in place of another for the same entity or term.
-
D.
isAbbreviation
Indicates that one term is a shortened or abbreviated form of another term.
-
E.
abbreviationUsedFor
Indicates that a particular shortened form or acronym is used to represent or stand in for a longer term, name, or expression.
- F. None of above.
Provenance (4 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. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26abb0ab08190b5bcf101c5680f3c |
completed | April 5, 2026, 1:59 p.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
Created at: March 30, 2026, 8:53 p.m.