Triple
T3691960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scream 4 |
E78362
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Anthony Anderson |
E166988
|
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: Anthony Anderson | Statement: [Scream 4, stars, Anthony Anderson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anthony Anderson Context triple: [Scream 4, stars, Anthony Anderson]
-
A.
Anthony Anderson
chosen
Anthony Anderson is an American actor and comedian known for his roles in film and television, including the hit sitcom "Black-ish."
-
B.
Mark Curtis
Mark Curtis is a British historian and author known for his critical works on UK foreign policy and Western interventionism.
-
C.
Rick Leary
Rick Leary is a Canadian public transit executive who serves as the chief executive officer of the Toronto Transit Commission, overseeing the city’s bus, streetcar, and subway operations.
-
D.
Bill Durnan
Bill Durnan was a Hall of Fame Canadian goaltender for the Montreal Canadiens in the 1940s, renowned for his ambidextrous catching ability and dominance in the early NHL.
-
E.
David Koechner
David Koechner is an American character actor and comedian best known for his scene-stealing roles in films like Anchorman and the TV series The Office.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e783a88190b2837a68b8723a25 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c688e0c8190a7e9ea3fe010c361 |
completed | March 14, 2026, 8:29 a.m. |
Created at: March 8, 2026, 3:26 p.m.