Triple
T19520360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maximals |
E488385
|
entity |
| Predicate | notableMember |
P10
|
FINISHED |
| Object | Cheetor |
—
|
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: Cheetor | Statement: [Maximals, notableMember, Cheetor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheetor Context triple: [Maximals, notableMember, Cheetor]
-
A.
Cheetor
chosen
Cheetor is a young, impulsive Maximal warrior from Transformers: Beast Wars who transforms into a cheetah and serves as one of the series’ primary heroic characters.
-
B.
Grimlock
Grimlock is a powerful Dinobot from the Transformers franchise, known for transforming into a mechanical Tyrannosaurus rex and his brutish strength and limited speech.
-
C.
Tobo
Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
-
D.
Prowler
Prowler is the high-tech, morally conflicted criminal alter ego of Aaron Davis in Marvel’s Spider-Man universe.
-
E.
Prowler
Prowler is a wooden roller coaster at the Worlds of Fun amusement park in Kansas City, Missouri, known for its fast, terrain-hugging layout through wooded areas.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359feb808190ba94563831adc720 |
completed | April 20, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.