Triple
T19446874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Levin |
E486500
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Charmcaster |
—
|
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: Charmcaster | Statement: [Kevin Levin, enemyOf, Charmcaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charmcaster Context triple: [Kevin Levin, enemyOf, Charmcaster]
-
A.
Charmcaster
chosen
Charmcaster is a recurring villain and powerful magic-wielding sorceress in the Ben 10 animated franchise.
-
B.
Sorceress
"Sorceress" is a jazz fusion composition by Return to Forever, known for its intricate rhythms, electric instrumentation, and virtuosic improvisation.
-
C.
Warlock
Warlock is the central character of the 1977 film "Handle with Care," around whom the movie’s narrative and conflicts revolve.
-
D.
Warlock
Warlock is a Hearthstone hero class themed around dark magic and demonic powers, often trading its own health for powerful cards and effects.
-
E.
Warlock
"Warlock" is a historical adventure novel by Wilbur Smith set in ancient Egypt, continuing the saga of the master strategist and mage Taita.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338a22608190bb31a1690ca0dab6 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.