Triple
T8728998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhattacharyya distance |
E207203
|
entity |
| Predicate | notProperty |
P45839
|
FINISHED |
| Object | metric in the strict mathematical sense |
—
|
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: metric in the strict mathematical sense | Statement: [Bhattacharyya distance, notProperty, metric in the strict mathematical sense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notProperty Context triple: [Bhattacharyya distance, notProperty, metric in the strict mathematical sense]
-
A.
notFunction
Indicates that the specified entity does not serve as a function or is not used in a functional role within the given context.
-
B.
notAbout
Indicates that a given entity, statement, or resource does not concern, reference, or pertain to another specified entity or topic.
-
C.
ownedProperty
Indicates that one entity possesses legal ownership or control over another entity as property.
-
D.
notDescribedAs
chosen
Indicates that an entity is explicitly not characterized, labeled, or referred to using a particular description or term.
-
E.
nonMaterialAspect
Indicates that one entity represents an immaterial, intangible, or conceptual aspect or property of another entity.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d19fdc88190860e0c9c93ab79ce |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.