Triple
T18564585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 1642 |
E453729
|
entity |
| Predicate | definesPropertyOfUTF-7 |
P132535
|
FINISHED |
| Object | ASCII text remains readable |
—
|
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: ASCII text remains readable | Statement: [RFC 1642, definesPropertyOfUTF-7, ASCII text remains readable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesPropertyOfUTF-7 Context triple: [RFC 1642, definesPropertyOfUTF-7, ASCII text remains readable]
-
A.
hasUnicodeProperty
Indicates that an entity possesses a specific Unicode character property or set of properties (such as category, script, or other Unicode-defined attributes).
-
B.
UnicodePlane
Indicates that a Unicode code point belongs to a specific Unicode plane (a contiguous range of code points grouped by plane number).
-
C.
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.
-
D.
definesCodepoint
Indicates that one entity specifies or assigns the particular codepoint value used to represent another entity in an encoding system.
-
E.
perceivedAsByCharacters
Indicates how something is viewed, interpreted, or understood by one or more characters.
- 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.