Triple
T28959058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atomic Food |
E731843
|
entity |
| Predicate | musicArtistCountry |
P71623
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Atomic Food, musicArtistCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicArtistCountry Context triple: [Atomic Food, musicArtistCountry, France]
-
A.
featuredArtistNationality
Indicates the nationality associated with an artist who is prominently featured in a work or event.
-
B.
hasCountryArtist
Indicates a relationship where an entity is associated with, represented by, or features a specific country music artist.
-
C.
associated artist nationality
chosen
Indicates the country or nationality with which an artist connected to the subject is identified.
-
D.
performingArtistNationality
Indicates the nationality or country of origin of the artist who performs a given work or performance.
-
E.
primaryArtistNationality
Indicates the nationality associated with the main or primary artist involved in a work 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 28, 2026, 8:49 a.m.