Triple
T19129863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan achieved income doubling ahead of schedule |
E468285
|
entity |
| Predicate | sourceCountryLanguage |
P2925
|
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: [Japan achieved income doubling ahead of schedule, sourceCountryLanguage, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceCountryLanguage Context triple: [Japan achieved income doubling ahead of schedule, sourceCountryLanguage, Japanese]
-
A.
countryOfLanguage
Indicates that a particular language is officially or predominantly used within a specified country.
-
B.
primaryLanguageCountry
Indicates that a given language is the main or officially predominant language used within a particular country.
-
C.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
D.
languageOfSources
chosen
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
E.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3e8c49481908b6be87af54d12cf |
completed | April 20, 2026, 8:29 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.