Triple
T33578994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haar measure |
E860100
|
entity |
| Predicate | invarianceType |
P9160
|
FINISHED |
| Object | left-invariant measure |
—
|
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: left-invariant measure | Statement: [Haar measure, invarianceType, left-invariant measure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: invarianceType Context triple: [Haar measure, invarianceType, left-invariant measure]
-
A.
invariantType
chosen
Indicates that one entity has a type or classification that remains constant or unchanged under specified conditions or transformations.
-
B.
invariantOf
Indicates that one element is an invariant (a property or quantity that remains unchanged) with respect to another element, system, or transformation.
-
C.
invariantUnder
Indicates that a property, structure, or quantity remains unchanged when a specified transformation or operation is applied.
-
D.
invariantTo
Indicates that one entity does not change in response to variations or transformations applied to another entity.
-
E.
invariantComparisonType
Indicates the specific way in which two invariants are compared or evaluated relative to each other.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f76e085c81909d71d6f47853cd12 |
completed | May 3, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.