Triple
T18048069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magic of Love |
E431844
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Do As Infinity |
—
|
NE NERFINISHED |
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: Do As Infinity | Statement: [Magic of Love, performer, Do As Infinity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Do As Infinity Context triple: [Magic of Love, performer, Do As Infinity]
-
A.
Do As Infinity
chosen
Do As Infinity is a Japanese pop-rock band known for their melodic rock sound and numerous anime and drama theme songs since their debut in the late 1990s.
-
B.
Lantis
Lantis is a Japanese music label and production company best known for producing and promoting music for anime, games, and voice actors.
-
C.
Usaka
Usaka is a town in the Ikwuano local government area of Abia State in southeastern Nigeria.
-
D.
Arashi
Arashi is a popular Japanese boy band formed under Johnny & Associates, known for their chart-topping J-pop hits, television appearances, and widespread influence in Japanese entertainment.
-
E.
Arashi
Arashi was an Imperial Japanese Navy destroyer that served in World War II, notably participating in several Pacific naval engagements before being sunk in 1943.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff39394819080407e1614bd5da9 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 10:25 a.m.