Triple
T34302462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hidden Markov Model |
E880217
|
entity |
| Predicate | hasObservableOutputs |
P141091
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hidden Markov Model, hasObservableOutputs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObservableOutputs Context triple: [Hidden Markov Model, hasObservableOutputs, yes]
-
A.
hasObservable
chosen
Indicates that an entity is associated with, or gives rise to, a measurable or perceivable outcome, property, or effect.
-
B.
hasOutputType
Indicates that an entity produces, returns, or yields a result of a specified type.
-
C.
hasOutputFeature
Indicates that an entity produces, exposes, or is associated with a particular output characteristic or feature as a result of its operation or behavior.
-
D.
isDirectlyObservable
Indicates that the subject can be perceived or measured directly without inference or intermediate interpretation.
-
E.
hasOutputDevice
Indicates that an entity is connected to or equipped with a particular output device used to present information or results.
- 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_69f349b79f6c81909cb468c92c39c74d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:57 a.m.