Triple
T14301118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Invasion of the Bane |
E354563
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Matthew Bouch |
E1068740
|
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: Matthew Bouch | Statement: [Invasion of the Bane, producer, Matthew Bouch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Bouch Context triple: [Invasion of the Bane, producer, Matthew Bouch]
-
A.
Matthew Bouch
chosen
Matthew Bouch is a television producer best known for his work on the British supernatural drama series "Being Human."
-
B.
Matthew McNulty
Matthew McNulty is a British actor known for his work in film and television, including roles in series like "Misfits," "The Mill," and "Versailles."
-
C.
Matthew Aldrich
Matthew Aldrich is an American screenwriter best known for co-writing Pixar’s Academy Award–winning animated film "Coco."
-
D.
Michael Boughen
Michael Boughen is a film producer known for his work on action and thriller movies, including the Jason Statham–starring film "Killer Elite."
-
E.
Matthew Betz
Matthew Betz was an American character actor of the silent and early sound film era, often cast in tough or villainous roles in numerous serials and B-movies.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717fc2348190bb6ba3109bd2871f |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d2883e081909c53170ef30b4125 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:11 a.m.