Triple
T30785217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenyan Sign Language |
E783937
|
entity |
| Predicate | usesFingerspellingFrom |
P26215
|
FINISHED |
| Object | English alphabet |
—
|
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: English alphabet | Statement: [Kenyan Sign Language, usesFingerspellingFrom, English alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFingerspellingFrom Context triple: [Kenyan Sign Language, usesFingerspellingFrom, English alphabet]
-
A.
usesFingerspellingSystem
chosen
Indicates that one entity employs or applies a particular fingerspelling system in communication or representation.
-
B.
usesSignLanguage
Indicates that one entity communicates using sign language with or in relation to another entity.
-
C.
recognizedSignLanguage
Indicates that one entity has correctly identified or understood a sign language used or produced by another entity.
-
D.
cannotBeEasilySpokenBy
Indicates that one entity (typically a word, phrase, or name) is difficult for another entity (typically a speaker or group) to pronounce or articulate smoothly.
-
E.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
- F. None of above.
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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 29, 2026, 8:41 p.m.