Triple
T19867978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boomerang France |
E477439
|
entity |
| Predicate | network |
P2637
|
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: [Boomerang France, network, Boomerang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boomerang Context triple: [Boomerang France, network, Boomerang]
-
A.
Boomerang
chosen
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 1992 romantic comedy film starring Eddie Murphy that follows a suave advertising executive whose womanizing ways are challenged when he meets his match.
-
C.
Boomerang
"Boomerang" is a 1998 puzzle-platform video game developed by The Creatures that features boomerang-based mechanics and environmental challenges.
-
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
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 (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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a0a7288190a82b85e3ae056d6b |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.