Triple
T26986494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleeping Beauty problem |
E679749
|
entity |
| Predicate | standardAnswer |
P77723
|
FINISHED |
| Object | thirder position |
—
|
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: thirder position | Statement: [Sleeping Beauty problem, standardAnswer, thirder position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardAnswer Context triple: [Sleeping Beauty problem, standardAnswer, thirder position]
-
A.
typicalAnswerType
Indicates the usual or expected kind of entity or value that serves as an answer to a given question or query.
-
B.
standardWithin
Indicates that one entity conforms to, or falls within the limits of, a specified standard defined by another entity.
-
C.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
D.
standardApproach
chosen
Indicates that an entity uses or follows a commonly accepted, conventional, or typical method for addressing a task or problem.
-
E.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 6:49 a.m.