Triple
T11411599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelfand transform |
E270383
|
entity |
| Predicate | mapsElementTo |
P9923
|
FINISHED |
| Object | its evaluation function on characters |
—
|
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: its evaluation function on characters | Statement: [Gelfand transform, mapsElementTo, its evaluation function on characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapsElementTo Context triple: [Gelfand transform, mapsElementTo, its evaluation function on characters]
-
A.
mapsTo
chosen
Indicates that one entity is associated with or transformed into another entity, typically defining a directional correspondence or function from a source to a target.
-
B.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
C.
mapsDepict
Indicates that maps visually represent or illustrate the geographic features, locations, or spatial relationships of something.
-
D.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
E.
mapped
Indicates that one entity has been associated, corresponded, or linked systematically to another according to some defined mapping or alignment.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8015017d08190b4020c76545556d6 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.