Triple
T5863902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get On Your Boots |
E130339
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | Magnificent |
E543023
|
NE 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: Magnificent | Statement: [Get On Your Boots, followedBy, Magnificent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magnificent Context triple: [Get On Your Boots, followedBy, Magnificent]
-
A.
Magnificent
chosen
"Magnificent" is a song by Irish rock band U2 from their 2009 album "No Line on the Horizon," known for its anthemic sound and prominent place in the band's live performances.
-
B.
Magnifique
Magnifique is a studio album by the American electronic rock duo Ratatat, known for its blend of guitar-driven melodies and synth-based production.
-
C.
Marvelous
Marvelous is the famous ring nickname of American boxing legend Marvin Hagler, one of the greatest middleweight champions in history.
-
D.
the Magnificent
"The Magnificent" is the renowned honorific epithet of Suleiman I, the long-reigning 16th-century Ottoman sultan celebrated for his military conquests, legal reforms, and cultural patronage.
-
E.
Regal
Regal is a major American movie theater chain known for operating multiplex cinemas across the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c035bdd698819089ffe5256df492aa |
completed | March 22, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b10b55a88190b525405b1e20ea77 |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:56 p.m.