Triple
T17889829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamlet 2 |
E447284
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Dana Marschz |
—
|
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: Dana Marschz | Statement: [Hamlet 2, hasCharacter, Dana Marschz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Marschz Context triple: [Hamlet 2, hasCharacter, Dana Marschz]
-
A.
Dana Marschz
chosen
Dana Marschz is a failed actor turned high school drama teacher whose misguided ambition to stage an outrageous sequel to "Hamlet" drives the satirical comedy of the film "Hamlet 2."
-
B.
Kim Schatzel
Kim Schatzel is an American academic administrator and business leader who serves as the president of the University of Louisville.
-
C.
Tana Schanzara
Tana Schanzara was a German actress known for her long-standing work in theater and film, particularly in comedic and character roles.
-
D.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
-
E.
Michaela Dorfmeister
Michaela Dorfmeister is a retired Austrian alpine ski racer renowned for winning multiple World Cup titles and Olympic gold medals in the early 2000s.
- 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_69d8b9f59bd48190a6fc925a855b8bac |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49d7828b481909b645fceb37a7ca3 |
completed | April 19, 2026, 9:16 a.m. |
Created at: April 10, 2026, 10:18 a.m.