Triple
T11002300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamiltonian Monte Carlo |
E260030
|
entity |
| Predicate | modelsStateWith |
P41880
|
FINISHED |
| Object | position variables |
—
|
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: position variables | Statement: [Hamiltonian Monte Carlo, modelsStateWith, position variables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelsStateWith Context triple: [Hamiltonian Monte Carlo, modelsStateWith, position variables]
-
A.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
B.
possibleModel
chosen
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
C.
associatedState
Indicates that one entity is linked or connected to a particular state, condition, or status of another entity.
-
D.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
E.
modernState
Indicates that an entity functions as a contemporary, currently existing state or nation in the modern era.
- 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_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. |
Created at: April 8, 2026, 9:25 p.m.