Triple
T21868912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braille |
E539952
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Chinese Braille |
—
|
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: Chinese Braille | Statement: [Braille, hasVariant, Chinese Braille]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chinese Braille Context triple: [Braille, hasVariant, Chinese Braille]
-
A.
Korean Braille
Korean Braille is the tactile writing system for the Korean language, designed to represent Hangul syllables in a format readable by touch for blind and visually impaired users.
-
B.
Braille
chosen
Braille is a tactile writing system using raised dots that enables blind and visually impaired people to read and write through touch.
-
C.
Zhuyin
Zhuyin is a phonetic writing system for transcribing the sounds of Mandarin Chinese, primarily used in Taiwan for teaching pronunciation and literacy.
-
D.
Armenian Braille
Armenian Braille is the tactile writing system used by blind and visually impaired readers to represent the Armenian language.
-
E.
Tai Nüa script
The Tai Nüa script is an abugida used primarily by the Tai Nüa (Dai) people of China and Southeast Asia to write the Tai Nüa language.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33305d081908cd070134420607a |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 6:57 p.m.