Triple
T18564531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-16 |
E453728
|
entity |
| Predicate | usesByteOrderMark |
P132531
|
FINISHED |
| Object | optional |
—
|
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: optional | Statement: [UTF-16, usesByteOrderMark, optional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesByteOrderMark Context triple: [UTF-16, usesByteOrderMark, optional]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
encodingIndependence
Indicates that a relationship or property holds regardless of the specific encoding or representation used for the involved entities.
-
C.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
D.
hasUnicodeStandard
Indicates that something conforms to, is defined by, or is associated with a particular version or aspect of the Unicode standard.
-
E.
encodedInUnicodeSince
Indicates that a given character or symbol has been included and assigned a code point in the Unicode standard starting from a specific version or time.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53afd8114819093b57d86f8213311 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:42 a.m.