Triple
T21718406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 6.1 |
E536089
|
entity |
| Predicate | addsSymbolCategory |
P44449
|
FINISHED |
| Object | pictographic symbols |
—
|
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: pictographic symbols | Statement: [Unicode 6.1, addsSymbolCategory, pictographic symbols]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsSymbolCategory Context triple: [Unicode 6.1, addsSymbolCategory, pictographic symbols]
-
A.
addsSymbolSet
Indicates that one entity augments another by including or appending a specified set of symbols to it.
-
B.
createsCategory
Indicates that one entity establishes or brings into existence a new category for organizing or classifying other entities.
-
C.
definesSymbol
Indicates that one entity specifies or establishes another entity as a symbol representing some concept, value, or object.
-
D.
addsClass
Indicates that one entity introduces or appends a class (such as a classification, type, or code) to another entity.
-
E.
introducedCategory
chosen
Indicates that an entity is responsible for bringing a particular category into use, recognition, or existence within a given context.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd96cc58081908dda09819041b888 |
completed | April 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.