Triple
T36132814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beggar Prince |
E1045067
|
entity |
| Predicate | featuresActorOfNationality |
P198156
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [The Beggar Prince, featuresActorOfNationality, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorOfNationality Context triple: [The Beggar Prince, featuresActorOfNationality, Japanese]
-
A.
hasLeadActorNationality
chosen
Indicates that the nationality of the lead actor in a work is a specified country or nationality.
-
B.
nationalityOfActor
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
C.
associatedActNationality
Indicates that an act, event, or action is connected to or characterized by a particular nationality.
-
D.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
E.
characterInFilmCountryOfOrigin
Indicates that a character appearing in a film is associated with the country where that film originated or was produced.
- 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_69f76e36a4508190b5bfc8f594272a4c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.