Triple
T18204905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mBART |
E435877
|
entity |
| Predicate | optimizationAlgorithm |
P27179
|
FINISHED |
| Object | Adam |
—
|
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: Adam | Statement: [mBART, optimizationAlgorithm, Adam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Context triple: [mBART, optimizationAlgorithm, Adam]
-
A.
Adam
Adam is a reclusive, centuries-old vampire musician and one of the two melancholic immortal lovers at the center of Jim Jarmusch’s film "Only Lovers Left Alive."
-
B.
Adam
Adam is a renowned sculpture by Auguste Rodin, notable for its expressive depiction of the biblical figure and housed in the Rodin Museum.
-
C.
Adam
Adam is a masculine given name of Hebrew origin, commonly used in many cultures and languages.
-
D.
Adam
chosen
Adam is a popular stochastic optimization algorithm widely used to train deep learning models by adaptively adjusting learning rates for each parameter.
-
E.
Adam
Adam is a widely used stochastic optimization algorithm in machine learning that combines ideas from momentum and adaptive learning rates to efficiently train deep neural networks.
- 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.