Triple
T17026081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Lucky Stars |
E413065
|
entity |
| Predicate | alternateLanguageVersion |
P123131
|
FINISHED |
| Object | Mandarin-dubbed version |
—
|
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: Mandarin-dubbed version | Statement: [My Lucky Stars, alternateLanguageVersion, Mandarin-dubbed version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternateLanguageVersion Context triple: [My Lucky Stars, alternateLanguageVersion, Mandarin-dubbed version]
-
A.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
B.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
workLanguageVariant
chosen
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
D.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
E.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d46a5081908bc5681621dd8534 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.