Triple
T18564560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 1642 |
E453729
|
entity |
| Predicate | defines |
P264
|
FINISHED |
| Object | UTF-7 |
—
|
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: UTF-7 | Statement: [RFC 1642, defines, UTF-7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UTF-7 Context triple: [RFC 1642, defines, UTF-7]
-
A.
UTF-7
chosen
UTF-7 is an obsolete, 7-bit Unicode text encoding designed primarily for safe transmission of Unicode data over email systems that were not fully 8-bit clean.
-
B.
UTF-8
UTF-8 is a widely used variable-length character encoding standard for Unicode that efficiently represents text in most of the world's writing systems while maintaining backward compatibility with ASCII.
-
C.
UTF-16
UTF-16 is a variable-length character encoding for Unicode that represents most common characters in one 16-bit code unit and others, including supplementary characters, in pairs of 16-bit code units.
-
D.
UTF-32
UTF-32 is a fixed-length Unicode character encoding that represents each code point using 32 bits, providing simple indexing at the cost of higher memory usage.
-
E.
UCS-2
UCS-2 is a fixed-length 16-bit character encoding that represents Unicode code points in the Basic Multilingual Plane, preceding and largely superseded by UTF-16.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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. |
Created at: April 10, 2026, 11:42 a.m.