Triple
T17399202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obihiro Racecourse |
E423040
|
entity |
| Predicate | languageOfOfficialCountry |
P95654
|
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: [Obihiro Racecourse, languageOfOfficialCountry, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOfficialCountry Context triple: [Obihiro Racecourse, languageOfOfficialCountry, Japanese]
-
A.
hasLanguageOfficial
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
B.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
C.
idiomasOficiales
Indicates that one or more languages are officially recognized or designated for use by a given entity (such as a country, region, or institution).
-
D.
hasOfficialCountryLanguage
chosen
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
E.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abf7ea08190a9d9f9358e3bb684 |
completed | April 19, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.