Triple
T23387512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PUA-A |
E593923
|
entity |
| Predicate | hasEncodingProperty |
P33682
|
FINISHED |
| Object | non-character-specific semantics |
—
|
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: non-character-specific semantics | Statement: [PUA-A, hasEncodingProperty, non-character-specific semantics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEncodingProperty Context triple: [PUA-A, hasEncodingProperty, non-character-specific semantics]
-
A.
hasMIMECharsetName
Indicates that an entity (such as a character encoding) is associated with a specific MIME charset name used in internet protocols.
-
B.
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.
-
C.
dataEncodingMethod
chosen
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
-
D.
hasDigitalEncoding
Indicates that one entity is represented, stored, or expressed using a specific digital code or encoding scheme provided by another entity.
-
E.
usesEncoder
Indicates that one entity employs or relies on an encoder component or mechanism to perform its function or process data.
- 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.