Triple
T20398199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meet Me After the Show |
E500262
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Karl Tunberg |
—
|
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: Karl Tunberg | Statement: [Meet Me After the Show, screenwriter, Karl Tunberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Tunberg Context triple: [Meet Me After the Show, screenwriter, Karl Tunberg]
-
A.
Karl Tunberg
chosen
Karl Tunberg was an American screenwriter best known for writing the screenplay of the epic 1959 film "Ben-Hur."
-
B.
William Tunberg
William Tunberg was an American screenwriter best known for adapting the classic 1957 Disney film "Old Yeller."
-
C.
Carl Kjeldsberg
Carl Kjeldsberg is a pathologist and academic leader best known as a co-founder of ARUP Laboratories, a major national clinical and anatomic pathology reference laboratory.
-
D.
Karl Engemann
Karl Engemann is an American music industry executive and talent manager best known for his long association with the Osmond family and other entertainment clients.
-
E.
Karl Sodersten
Karl Sodersten is a film editor known for his work on the Australian psychological thriller "Lantana."
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798c2b28819092fab93f01218cde |
completed | April 20, 2026, 7:07 p.m. |
Created at: April 16, 2026, 11:29 a.m.