Triple
T15625006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RED (2010 film) |
E375656
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Robert Schwentke |
E134598
|
NE FINISHED |
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: Robert Schwentke | Statement: [RED (2010 film), director, Robert Schwentke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Schwentke Context triple: [RED (2010 film), director, Robert Schwentke]
-
A.
Robert Schwentke
chosen
Robert Schwentke is a German film director and screenwriter known for directing Hollywood thrillers and action films such as "Flightplan," "RED," and "The Time Traveler's Wife."
-
B.
Rolf Weitz
Rolf Weitz is an individual notable enough to be specifically cited as a bearer of the surname Weitz.
-
C.
Stephan Jost
Stephan Jost is a Canadian art museum director best known for leading the Art Gallery of Ontario in Toronto.
-
D.
Markus Majowski
Markus Majowski is a German actor and comedian known for his roles in film, television, and theater.
-
E.
Thomas Spies
Thomas Spies is a German politician and member of the Social Democratic Party (SPD) who has served as the mayor of Marburg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9e5e248190ae54cda1fde51efb |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3f65dc8190ac94db1d4d53d77f |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:14 a.m.