Triple
T36133195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gray Horizon |
E1045080
|
entity |
| Predicate | hasDirectorOfNationality |
P22097
|
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 Gray Horizon, hasDirectorOfNationality, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectorOfNationality Context triple: [The Gray Horizon, hasDirectorOfNationality, Japanese]
-
A.
hasDirectorNationality
chosen
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
B.
hasLeadActorNationality
Indicates that the nationality of the lead actor in a work is a specified country or nationality.
-
C.
hasCinematographerNationality
Indicates that a cinematographer is associated with a specific nationality.
-
D.
hasCastMemberNationality
Indicates that at least one cast member of a work has the specified nationality.
-
E.
hasDirectorStar
Indicates that a person both directed and starred in the same work (e.g., film, show, or production).
- 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_69ff53389a0481908b2baeb43c6294f0 |
completed | May 9, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69ff52e2b4b88190b38d160d771fe14b |
completed | May 9, 2026, 3:29 p.m. |
Created at: May 3, 2026, 4:08 p.m.