Triple
T34786932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laplace's rule of succession |
E1002836
|
entity |
| Predicate | usesPrior |
P190383
|
FINISHED |
| Object | uniform prior on probability parameter |
—
|
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: uniform prior on probability parameter | Statement: [Laplace's rule of succession, usesPrior, uniform prior on probability parameter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPrior Context triple: [Laplace's rule of succession, usesPrior, uniform prior on probability parameter]
-
A.
priorPost
Indicates that one post occurs earlier in sequence or time relative to another post.
-
B.
wasPriorOf
Indicates that one entity held a position, role, or status before another entity in a temporal or sequential order.
-
C.
priorService
Indicates that one entity has previously provided service or served in a role, position, or capacity before the current context or event.
-
D.
oftenUsePrior
Indicates that an entity frequently relies on or applies prior information, methods, or experiences in a given context.
-
E.
usedBefore
Indicates that one entity was utilized or applied prior to the use or occurrence of another entity.
- F. None of above. chosen
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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: May 3, 2026, 3:59 p.m.