Triple
T8111068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Take |
E189351
|
entity |
| Predicate | hasEditor |
P1954
|
FINISHED |
| Object | Peter Roeck |
E189351
|
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: Peter Roeck | Statement: [The Take, hasEditor, Peter Roeck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Roeck Context triple: [The Take, hasEditor, Peter Roeck]
-
A.
Peter Roeck
chosen
Peter Roeck is a film editor known for his work on the movie "The Take."
-
B.
Peter Welinder
Peter Welinder is a computer scientist and entrepreneur known for his contributions to deep reinforcement learning and for co-authoring the Hindsight Experience Replay technique.
-
C.
Thomas Rongen
Thomas Rongen is a Dutch-American soccer coach and former player known for his extensive coaching career in Major League Soccer and with various U.S. national youth teams.
-
D.
Peter Noorwits
Peter Noorwits was a Dutch architect known for his work on prominent ecclesiastical buildings in the Netherlands, including the Nieuwe Kerk in The Hague.
-
E.
Richard Heus
Richard Heus is a television producer best known for serving as an executive producer on the acclaimed alternate-history series "The Man in the High Castle."
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42fcfb9c81908496f9a7e30d0d8a |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbe994fc881908a43cfdf9f28753c |
completed | April 1, 2026, 6:43 a.m. |
Created at: March 30, 2026, 5:32 p.m.