Triple
T6991528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-8 |
E162096
|
entity |
| Predicate | backwardCompatibleWith |
P4635
|
FINISHED |
| Object | ASCII |
E23922
|
NE 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 | Statement: [UTF-8, backwardCompatibleWith, ASCII]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ASCII Context triple: [UTF-8, backwardCompatibleWith, ASCII]
-
A.
ASCII
chosen
ASCII is a widely used character encoding standard that represents text in computers and other devices using 7-bit numerical codes for letters, digits, punctuation, and control characters.
-
B.
ISO 646
ISO 646 is an international standard for 7-bit character encodings that defines a set of basic Latin characters and allows national variants, serving as a foundation for many early computer character sets.
-
C.
ASCI
ASCI is a prestigious U.S. honor society of physician-scientists dedicated to advancing clinical and translational research.
-
D.
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.
-
E.
Unicode
Unicode is a universal character encoding standard that assigns unique code points to virtually all written scripts, symbols, and emojis used in modern computing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc1f63c8190837cfd71cf5ed613 |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761d6ed5481909ccf1650fe6dc747 |
completed | March 28, 2026, 5:06 a.m. |
Created at: March 27, 2026, 2:32 p.m.