Triple
T22533550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ガーター勲章 |
E557101
|
entity |
| Predicate | モットー言語 |
P123203
|
FINISHED |
| Object | 古フランス語 |
—
|
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: 古フランス語 | Statement: [ガーター勲章, モットー言語, 古フランス語]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: モットー言語 Context triple: [ガーター勲章, モットー言語, 古フランス語]
-
A.
мова
chosen
Indicates that an entity uses, is expressed in, or is associated with a particular language.
-
B.
hasLanguageFormOf
Indicates that one entity is a specific linguistic form, expression, or realization of the language used by another entity.
-
C.
fictionalLanguage
Indicates a relationship where an entity uses, is expressed in, or is associated with a language that is invented or does not exist in reality.
-
D.
lexifierLanguage
Indicates that one language serves as the primary source or base language from which the core vocabulary and structure of another language, typically a pidgin or creole, are derived.
-
E.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed88cf08190ae7e5b6bf9a80372 |
completed | April 29, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.