Triple
T23387481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCS-2 |
E593922
|
entity |
| Predicate | byteOrderMarkUsage |
P132531
|
FINISHED |
| Object | may use BOM to indicate endianness |
—
|
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: may use BOM to indicate endianness | Statement: [UCS-2, byteOrderMarkUsage, may use BOM to indicate endianness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: byteOrderMarkUsage Context triple: [UCS-2, byteOrderMarkUsage, may use BOM to indicate endianness]
-
A.
usesByteOrderMark
chosen
Indicates that a text or data stream includes a byte order mark (BOM) to specify its encoding or endianness.
-
B.
byteOrderMarkCodeUnit
Indicates the specific code unit value used to represent a byte order mark (BOM) in an encoded text sequence.
-
C.
encodingIndependence
Indicates that a relationship or property holds regardless of the specific encoding or representation used for the involved entities.
-
D.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
E.
hasUnicodeStandard
Indicates that something conforms to, is defined by, or is associated with a particular version or aspect of the Unicode standard.
- 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a498fd08819085e90a872d9d0c7a |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:35 p.m.