Triple
T32747312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jensen–Shannon divergence |
E837388
|
entity |
| Predicate | canBeExpressedUsingEntropy |
P12675
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jensen–Shannon divergence, canBeExpressedUsingEntropy, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeExpressedUsingEntropy Context triple: [Jensen–Shannon divergence, canBeExpressedUsingEntropy, true]
-
A.
usesEntropyCoding
Indicates that one entity applies entropy coding techniques to process, compress, or represent data associated with another entity.
-
B.
hasEntropy
Indicates that an entity possesses or is characterized by a certain amount or state of entropy, typically reflecting its degree of disorder or uncertainty.
-
C.
cannotBeExpressedInTermsOf
Indicates that one entity or concept cannot be fully defined, derived, or represented using only the other entity or concept.
-
D.
entropyTermDependsOn
Indicates that the value of an entropy term is functionally dependent on another specified quantity or set of variables.
-
E.
mathematicallyExpressedBy
chosen
Indicates that something (such as a concept, quantity, or relationship) is represented or captured using a specific mathematical expression or formulation.
- 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_69f34936e1748190b797e406e4e9293a |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: May 1, 2026, 1:12 a.m.