Triple
T11002303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamiltonian Monte Carlo |
E260030
|
entity |
| Predicate | targetDistribution |
P96952
|
FINISHED |
| Object | posterior distribution |
—
|
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: posterior distribution | Statement: [Hamiltonian Monte Carlo, targetDistribution, posterior distribution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDistribution Context triple: [Hamiltonian Monte Carlo, targetDistribution, posterior distribution]
-
A.
distributionBy
Indicates how something is allocated, arranged, or spread according to a specified criterion or grouping.
-
B.
distributesIn
Indicates that one entity allocates or hands out something (e.g., items, resources, information) within or across a specified area, group, or context.
-
C.
distribution
Indicates the act or pattern of giving, delivering, or spreading something from one source to multiple recipients or locations.
-
D.
distributedAs
Indicates that something is allocated, delivered, or spread out according to a particular pattern, rule, or distribution scheme.
-
E.
distributionHub
Indicates a location or facility that serves as a central point for receiving, sorting, and redistributing goods or resources to multiple destinations.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d796d760008190930228fa77b61b8b |
completed | April 9, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d733b27ffc81908ab1b8df198cd5c7 |
completed | April 9, 2026, 5:05 a.m. |
Created at: April 8, 2026, 9:25 p.m.