Triple
T30442475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo (Narita) – Hong Kong |
E774486
|
entity |
| Predicate | languageAtOrigin |
P1754
|
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 (Narita) – Hong Kong, languageAtOrigin, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAtOrigin Context triple: [Tokyo (Narita) – Hong Kong, languageAtOrigin, Japanese]
-
A.
indirectOriginLanguage
Indicates that something originates from a particular language, not directly but through one or more intermediate languages or sources.
-
B.
hasLanguageOfOrigin
chosen
Indicates that one entity has its origin or source in the language specified by another entity.
-
C.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
D.
languageOfOriginalReport
Indicates the language in which the original report was written or produced.
-
E.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
- 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_69f22493ef9c8190ae8c2afcb7f994c8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
Created at: April 29, 2026, 8:08 p.m.