Triple
T16546943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodan (1956 film) |
E401966
|
entity |
| Predicate | hasEnglishDubbedVersion |
P43395
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Rodan (1956 film), hasEnglishDubbedVersion, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishDubbedVersion Context triple: [Rodan (1956 film), hasEnglishDubbedVersion, yes]
-
A.
languageDubbedIn
Indicates that the content’s audio has been dubbed into the specified language.
-
B.
hasEnglishEdition
chosen
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
C.
hasKoreanVersion
Indicates that something has a corresponding version or counterpart that is in the Korean language.
-
D.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
E.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fbe3fb48190bad143b50dc73c7e |
completed | April 18, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.