Triple
T10427339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBC BASIC |
E245819
|
entity |
| Predicate | characterSetSupport |
P7661
|
FINISHED |
| Object | ASCII |
—
|
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: ASCII | Statement: [BBC BASIC, characterSetSupport, ASCII]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterSetSupport Context triple: [BBC BASIC, characterSetSupport, ASCII]
-
A.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
B.
characterSetSize
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
C.
usesCharacterSet
chosen
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
D.
characterCoverage
Indicates that one entity provides or includes sufficient representation or support for the characters (e.g., glyphs, symbols, or scripts) required or used by another entity.
-
E.
supportsUnicode
Indicates that an entity is capable of correctly handling, storing, or displaying Unicode-encoded text.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea498ab08190b451c0b257c0711b |
completed | April 7, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:12 p.m.