Triple
T13120202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ice Land |
E311699
|
entity |
| Predicate | hasEnemyType |
P15619
|
FINISHED |
| Object | Boomerang Bro |
E311691
|
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: Boomerang Bro | Statement: [Ice Land, hasEnemyType, Boomerang Bro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boomerang Bro Context triple: [Ice Land, hasEnemyType, Boomerang Bro]
-
A.
Boomerang Bro
chosen
Boomerang Bro is a recurring Koopa enemy in the Mario series known for attacking by throwing boomerangs in arcing patterns.
-
B.
Boomerang!
Boomerang! is a 1947 American film noir crime drama noted for its semi-documentary style and exploration of a real-life wrongful murder accusation.
-
C.
Boomerang II
Boomerang II is a lesser-known track by Irish rock band U2, released as a B-side during their mid-1980s era.
-
D.
Boomerang
Boomerang is a television network known for airing classic and contemporary animated programming, particularly cartoons from the Warner Bros. and Hanna-Barbera libraries.
-
E.
Boomerang
Boomerang is a steel shuttle roller coaster known for its forward-and-backward looping layout, operating at the Worlds of Fun amusement park in Kansas City, Missouri.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98196e69081909111407ee3d9f08e |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5d205408190883b67739d5efaa7 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:06 p.m.