Triple
T736695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minkowski functional |
E14948
|
entity |
| Predicate | associatesToEachSet |
P2830
|
FINISHED |
| Object | a sublinear functional |
—
|
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: a sublinear functional | Statement: [Minkowski functional, associatesToEachSet, a sublinear functional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatesToEachSet Context triple: [Minkowski functional, associatesToEachSet, a sublinear functional]
-
A.
sets
Indicates that an entity places, positions, or puts another entity into a particular state, location, or configuration.
-
B.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
C.
participatingAssociations
Indicates that certain associations are involved as participants in a given activity, event, or relationship.
-
D.
hasMemberFromEach
Indicates that a group or collection includes at least one member originating from each specified category, set, or subgroup.
-
E.
associatedWithSettlement
Indicates a relationship where an entity is linked or connected to a particular settlement, such as a town, village, or city.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.