Triple
T575105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Java |
E13745
|
entity |
| Predicate | defaultCharacterEncoding |
P7661
|
FINISHED |
| Object | UTF-16 for String internal representation |
—
|
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: UTF-16 for String internal representation | Statement: [Java, defaultCharacterEncoding, UTF-16 for String internal representation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defaultCharacterEncoding Context triple: [Java, defaultCharacterEncoding, UTF-16 for String internal representation]
-
A.
usesCharacterSet
chosen
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
C.
defaultFileSystem
Indicates that a given file system is the primary or standard file system automatically used by default for file operations in a particular context.
-
D.
codingSystemContext
Indicates the coding system or classification framework within which a given code, identifier, or value is defined and interpreted.
-
E.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b4c23548190a3b883239c7c78c8 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.