Triple
T31131175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 12.0 |
E793510
|
entity |
| Predicate | definesCharacterEncodingModel |
P194424
|
FINISHED |
| Object | Unicode character encoding |
—
|
NE NERFINISHED |
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: Unicode character encoding | Statement: [Unicode 12.0, definesCharacterEncodingModel, Unicode character encoding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesCharacterEncodingModel Context triple: [Unicode 12.0, definesCharacterEncodingModel, Unicode character encoding]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
codingSystemType
Indicates the classification or category of coding system used to encode or represent information in a given context.
-
C.
usesEncodingRules
Indicates that one entity applies or conforms to a specified set of encoding rules when representing or transforming information.
-
D.
localEncoding
Indicates that an entity is represented or stored using a specific encoding scheme that is defined or applied locally within a particular context or system.
-
E.
encodingIs
Indicates that one entity serves as the specific encoding or coded representation of another entity.
- F. None of above. chosen
Provenance (4 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
| PDg | Predicate description generation | batch_69fd6f9a8bd881909983fe8f4cd0ba98 |
completed | May 8, 2026, 5:07 a.m. |
Created at: April 29, 2026, 9:05 p.m.