Triple
T13428961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crottin de Chavignol |
E313555
|
entity |
| Predicate | originCountryLanguage |
P42614
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Crottin de Chavignol, originCountryLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originCountryLanguage Context triple: [Crottin de Chavignol, originCountryLanguage, French]
-
A.
originalLanguageCountry
chosen
Indicates the country where a work’s original language is primarily spoken or officially used.
-
B.
laterCountryOfOrigin
Indicates that an entity’s country of origin changed, and this predicate specifies the country that became its origin at a later time than a previously associated country.
-
C.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
D.
originalNationality
Indicates the country or nationality an entity initially belonged to or originated from, before any later changes in citizenship or affiliation.
-
E.
nativeCountry
Indicates the country in which an entity (typically a person) was born or is originally from.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed304ac8190a8021f749de8164c |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.