Triple
T8628408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thor: Love and Thunder |
E204335
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Matthew Schmidt |
E239842
|
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 Schmidt | Statement: [Thor: Love and Thunder, editedBy, Matthew Schmidt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Schmidt Context triple: [Thor: Love and Thunder, editedBy, Matthew Schmidt]
-
A.
Matthew Schmidt
chosen
Matthew Schmidt is a film editor best known for his work on major Marvel Cinematic Universe films, including Avengers: Infinity War.
-
B.
Christopher Schmidt
Christopher Schmidt is the real name of the DC Comics antihero Peacemaker, a vigilante obsessed with achieving peace through often extreme and violent means.
-
C.
John Luessenhop
John Luessenhop is an American film director and screenwriter best known for helming genre and action films, including the horror sequel "Texas Chainsaw 3D."
-
D.
Ken Schretzmann
Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
-
E.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc473f6b888190ae40d65f24122c88 |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb759f6c819085939e38e0281361 |
completed | April 3, 2026, 3:23 p.m. |
Created at: March 30, 2026, 6:27 p.m.