Triple
T22963156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evolution |
E570961
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Boomerang |
—
|
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: Boomerang | Statement: [Evolution, hasTrack, Boomerang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boomerang Context triple: [Evolution, hasTrack, Boomerang]
-
A.
Boomerang
Boomerang is a television network known for airing classic and contemporary animated programming, particularly cartoons from the Warner Bros. and Hanna-Barbera libraries.
-
B.
Boomerang
"Boomerang" is a 1998 puzzle-platform video game developed by The Creatures that features boomerang-based mechanics and environmental challenges.
-
C.
Boomerang
Boomerang is a non-fiction book by Michael Lewis that explores the fallout of the global financial crisis through vivid reporting on several heavily affected countries.
-
D.
Boomerang
Boomerang is a 1974 video art piece by American artist Nancy Holt that explores perception, time delay, and self-awareness through closed-circuit television.
-
E.
Boomerang
chosen
Boomerang is a Marvel Comics supervillain and frequent Spider-Man adversary known for his deadly, high-tech boomerang weapons and mercenary background.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f66fbc8190a4a7b73d17537132 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.