Triple
T18204521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ALBERT |
E435869
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | ALBERT-xxlarge |
—
|
NE NERFINISHED |
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: ALBERT-xxlarge | Statement: [ALBERT, hasVariant, ALBERT-xxlarge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ALBERT-xxlarge Context triple: [ALBERT, hasVariant, ALBERT-xxlarge]
-
A.
ALBERT-xlarge
chosen
ALBERT-xlarge is a large-scale variant of the ALBERT language model architecture, designed to provide stronger natural language understanding performance through increased model capacity and depth.
-
B.
ALBERT-large
ALBERT-large is a larger, higher-capacity configuration of the ALBERT language model designed to improve performance on natural language understanding tasks while maintaining parameter efficiency.
-
C.
ALBERT-base
ALBERT-base is a smaller, base-sized configuration of the ALBERT language model designed to provide efficient natural language understanding with reduced parameters and memory usage.
-
D.
GPT-NeoX-20B
GPT-NeoX-20B is a 20-billion-parameter open-source large language model developed by EleutherAI as a powerful successor to the GPT-Neo family for advanced text generation and research.
-
E.
Megatron-LM
Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.