Triple
T20153158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzy Berhow |
E491486
|
entity |
| Predicate | hasYouTubeChannel |
P8080
|
FINISHED |
| Object | Mortem3r |
—
|
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: Mortem3r | Statement: [Suzy Berhow, hasYouTubeChannel, Mortem3r]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mortem3r Context triple: [Suzy Berhow, hasYouTubeChannel, Mortem3r]
-
A.
Mortem3r
chosen
Mortem3r is the online alias of Suzy Berhow, an American YouTuber, artist, and former co-host of the Game Grumps–related channel KittyKatGaming.
-
B.
Mortus
Mortus is the main villain of the 1995 Sega Genesis beat ’em up game Comix Zone, a demonic comic-book creator who brings his own drawings to life to battle the hero.
-
C.
Mortician
Mortician is an American death metal band known for its extremely brutal sound, horror movie samples, and association with the underground extreme metal scene.
-
D.
de Mortemart
De Mortemart is the noble French family name of Madame de Montespan, a prominent 17th-century courtier and mistress of King Louis XIV.
-
E.
Morta
Morta is the Roman goddess of death and destiny, one of the three Fates who determines the moment of each mortal’s death by cutting the thread of life.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667dda9b4819097ff66bb2b50fc21 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.