Triple
T43360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame X |
E852
|
entity |
| Predicate | artistNationality |
P2
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Madame X, artistNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artistNationality Context triple: [Madame X, artistNationality, American]
-
A.
nationalityRepresented
Indicates the country or nation that an entity officially represents, typically in a professional, competitive, or diplomatic capacity.
-
B.
notableArtist
Indicates that the subject is an artist who is widely recognized or distinguished for their work.
-
C.
countryRepresented
Indicates that one entity serves as the official representative (such as an athlete, diplomat, or delegate) of a specific country in a given context or event.
-
D.
formerCountry
Indicates that an entity was previously recognized as a country but no longer holds that status.
-
E.
countryOfCitizenship
chosen
Indicates the country in which a person or entity holds legal citizenship.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24c083ad081909c1122c8fb29efdc |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24aba9a2c81909f769a8f22e30c92 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.