Triple
T24148850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 8859-13 |
E598468
|
entity |
| Predicate | definesCodePointsFor |
P154786
|
FINISHED |
| Object | 256 characters |
—
|
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: 256 characters | Statement: [ISO/IEC 8859-13, definesCodePointsFor, 256 characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesCodePointsFor Context triple: [ISO/IEC 8859-13, definesCodePointsFor, 256 characters]
-
A.
definesCodepoint
Indicates that one entity specifies or assigns the particular codepoint value used to represent another entity in an encoding system.
-
B.
usesCodePoints
Indicates that one entity represents, encodes, or operates using the specific set of Unicode code points defined by another entity.
-
C.
hasUnicodeCodePoint
Indicates that a character or symbol is associated with a specific numeric Unicode code point value.
-
D.
codePointType
Indicates the classification or category assigned to a specific Unicode code point (such as letter, digit, punctuation, etc.).
-
E.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
- 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_69e288c9e488819093dd1acd91b08b8a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e00d252c8190a02bec29189baad0 |
completed | April 29, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 11:30 p.m.