Triple
T28498824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metropolitan Routes |
E721178
|
entity |
| Predicate | signLanguage |
P4196
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [Tokyo Metropolitan Routes, signLanguage, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signLanguage Context triple: [Tokyo Metropolitan Routes, signLanguage, Japanese]
-
A.
recognizedSignLanguage
Indicates that one entity has correctly identified or understood a sign language used or produced by another entity.
-
B.
usesSignLanguage
Indicates that one entity communicates using sign language with or in relation to another entity.
-
C.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
-
D.
callSignLanguage
Indicates that one entity communicates with another using sign language as the medium of the call or conversation.
-
E.
languageOfSignatures
Indicates the language in which the signatures on a document or agreement are written or expressed.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64f416c1481909dd3eed650cce660 |
completed | May 2, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:05 a.m.