Triple
T10323808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let Me In |
E242707
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Stan Salfas |
E434836
|
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: Stan Salfas | Statement: [Let Me In, editedBy, Stan Salfas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Salfas Context triple: [Let Me In, editedBy, Stan Salfas]
-
A.
Stan Salfas
chosen
Stan Salfas is a film editor known for his work on major feature films, including the science fiction sequel "Dawn of the Planet of the Apes."
-
B.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
C.
Tom Schaul
Tom Schaul is a machine learning researcher known for his contributions to deep reinforcement learning, including co-developing the Dueling DQN architecture.
-
D.
Ben Fankhauser
Ben Fankhauser is an American stage actor and singer best known for originating the role of Davey in the Broadway production of the musical "Newsies."
-
E.
Joe Sahlen
Joe Sahlen is an American businessman best known as the owner of the Western New York Flash professional soccer club.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6ce683c8190bf5385dd04bf2de8 |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e215e3c3c88190833c1f56288629a2 |
completed | April 17, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:50 a.m.