Triple
T28616212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SetEnvironmentVariable |
E724278
|
entity |
| Predicate | supportsCharacterEncoding |
P7661
|
FINISHED |
| Object | ANSI |
—
|
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: ANSI | Statement: [SetEnvironmentVariable, supportsCharacterEncoding, ANSI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCharacterEncoding Context triple: [SetEnvironmentVariable, supportsCharacterEncoding, ANSI]
-
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.
hasExtendedCharacterSet
Indicates that an entity supports or uses a character set that goes beyond a basic or standard set of characters.
-
C.
definesCharacterEncodingModel
Indicates that an entity specifies or establishes the character encoding scheme used by a particular model.
-
D.
supportsCharacterDifferences
Indicates that one entity accepts, encourages, or positively reinforces differences in traits, identities, or characteristics between characters.
-
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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a016336c58081909c58c5772e6fb488 |
completed | May 11, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_6a0160f25d8081909a6aaa375e9850b0 |
completed | May 11, 2026, 4:54 a.m. |
Created at: April 28, 2026, 4:32 a.m.