Triple
T24649097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supplemental Mathematical Operators |
E610196
|
entity |
| Predicate | containsExampleCharacter |
P5716
|
FINISHED |
| Object | U+2A00 N-ARY CIRCLED DOT OPERATOR |
—
|
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: U+2A00 N-ARY CIRCLED DOT OPERATOR | Statement: [Supplemental Mathematical Operators, containsExampleCharacter, U+2A00 N-ARY CIRCLED DOT OPERATOR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsExampleCharacter Context triple: [Supplemental Mathematical Operators, containsExampleCharacter, U+2A00 N-ARY CIRCLED DOT OPERATOR]
-
A.
containsCharacter
chosen
Indicates that one entity includes a specific character as part of its content or composition.
-
B.
containsCharacterAction
Indicates that an entity includes or features an action performed by a character within it.
-
C.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
D.
hasImaginaryCharacter
Indicates that an entity includes, features, or is associated with a fictional or imaginary character.
-
E.
hasComponentCharacter
Indicates that one entity includes another entity as a constituent character or symbolic component.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:33 a.m.