Triple
T20229284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTV Europe Music Award for Best Alternative |
E495471
|
entity |
| Predicate | hasNotableWinner |
P2766
|
FINISHED |
| Object | Muse |
—
|
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: Muse | Statement: [MTV Europe Music Award for Best Alternative, hasNotableWinner, Muse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muse Context triple: [MTV Europe Music Award for Best Alternative, hasNotableWinner, Muse]
-
A.
Muse
Muse is a major border town in Myanmar’s Shan State that serves as a key trade gateway between Myanmar and China.
-
B.
Muse
chosen
Muse is a British rock band known for its dramatic fusion of alternative rock, progressive elements, and electronic influences, as well as its theatrical live performances.
-
C.
Muse
Muse is a masculine given name most notably borne by American actor Muse Watson.
-
D.
Muse
Muse is a small unincorporated community located in Washington County, Pennsylvania, United States.
-
E.
MUSE
MUSE is an advanced integral-field spectrograph used in optical astronomy to capture detailed spatial and spectral information from celestial objects.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fdc2590819089a946d16c6c0e59 |
completed | April 20, 2026, 6:26 p.m. |
Created at: April 11, 2026, 11:39 p.m.