Triple
T10023657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto-Encoding Variational Bayes |
E200670
|
entity |
| Predicate | definesObjective |
P38243
|
FINISHED |
| Object | evidence lower bound |
—
|
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: evidence lower bound | Statement: [Auto-Encoding Variational Bayes, definesObjective, evidence lower bound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesObjective Context triple: [Auto-Encoding Variational Bayes, definesObjective, evidence lower bound]
-
A.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
B.
definesAimsOf
chosen
Indicates that one entity specifies or establishes the goals, purposes, or intended outcomes of another entity.
-
C.
actorObjective
Indicates that an actor has a specific goal, purpose, or intended outcome in relation to another entity or situation.
-
D.
objectiveIncludes
Indicates that a broader objective encompasses or contains a specific sub-objective, component, or element as part of its scope.
-
E.
fundingObjective
Indicates the purpose or goal for which financial resources are being sought, allocated, or used.
- 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.