Triple
T10514907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The New Tenants |
E248006
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Alan Baumgarten |
E250522
|
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: Alan Baumgarten | Statement: [The New Tenants, editor, Alan Baumgarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alan Baumgarten Context triple: [The New Tenants, editor, Alan Baumgarten]
-
A.
Alan Baumgarten
chosen
Alan Baumgarten is an American film editor known for his work on a variety of feature films and television projects.
-
B.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
-
C.
Michael Greenberg
Michael Greenberg is a prominent American neuroscientist renowned for his pioneering work on activity-dependent gene expression in the brain.
-
D.
Michael Greenberg
Michael Greenberg is an American businessman best known as the co-founder and longtime executive leader of the global footwear company Skechers.
-
E.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cbacb08190a446c864b97823ad |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e877c6188190817fb30f2c9a07bf |
completed | April 20, 2026, 8:48 a.m. |
Created at: April 6, 2026, 12:27 p.m.