Triple
T21618270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All I Want for Christmas Is You |
E533502
|
entity |
| Predicate | hasJapaneseVersion |
P61159
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [All I Want for Christmas Is You, hasJapaneseVersion, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJapaneseVersion Context triple: [All I Want for Christmas Is You, hasJapaneseVersion, true]
-
A.
hasKoreanVersion
Indicates that something has a corresponding version or counterpart that is in the Korean language.
-
B.
hasJapaneseText
Indicates that an entity contains or is associated with text written in the Japanese language.
-
C.
japaneseVariant
chosen
Indicates that one entity is a Japanese-language or Japan-specific variant or version of another entity.
-
D.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
E.
hasChineseVersion
Indicates that an entity has a corresponding version or representation available in Chinese.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3bac4a5c8190919c625c14a54c16 |
completed | April 27, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.