Triple
T25853838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Barbarian and the Geisha |
E651286
|
entity |
| Predicate | featuresCharacterNationality |
P15237
|
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: [The Barbarian and the Geisha, featuresCharacterNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterNationality Context triple: [The Barbarian and the Geisha, featuresCharacterNationality, American]
-
A.
featuresNationality
Indicates that an entity includes, presents, or is associated with a particular nationality.
-
B.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
C.
nationalityInStory
chosen
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
-
D.
workerNationality
Indicates the country or nationality to which a worker belongs or is legally associated.
-
E.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 22, 2026, 7:59 a.m.