Triple
T10813997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saitama Prefectural flag |
E255176
|
entity |
| Predicate | languageRepresented |
P30204
|
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: [Saitama Prefectural flag, languageRepresented, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRepresented Context triple: [Saitama Prefectural flag, languageRepresented, Japanese]
-
A.
hasLanguageRepresentation
chosen
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
B.
languageGroupSpoken
Indicates that a particular language group is spoken or used for communication by an entity.
-
C.
hasRepresentativeLanguage
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
D.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
E.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eba9b48190b4dbe7fe5d8be0a4 |
completed | April 9, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:18 p.m.