Triple
T6067511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep Impact |
E135196
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Mimi Leder |
E450461
|
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: Mimi Leder | Statement: [Deep Impact, director, Mimi Leder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mimi Leder Context triple: [Deep Impact, director, Mimi Leder]
-
A.
Mimi Leder
chosen
Mimi Leder is an American film and television director and producer known for her work on impactful dramas such as "Deep Impact," "The Leftovers," and "On the Basis of Sex."
-
B.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
-
C.
Michelle Trachtenberg
Michelle Trachtenberg is an American actress best known for her role as Dawn Summers on the television series "Buffy the Vampire Slayer."
-
D.
Ellen Mirojnick
Ellen Mirojnick is an American costume designer known for her influential work on films such as "Basic Instinct" and numerous other high-profile productions.
-
E.
Eleanor Zellman
Eleanor Zellman, better known by her stage name Eleanor Audley, was an American actress famed for her distinctive voice work in classic Disney films and for roles in mid-20th-century radio 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057403a8081908b593472fcc0d699 |
completed | March 22, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65faa58208190a44af8f9b26ddaf0 |
completed | March 27, 2026, 10:44 a.m. |
Created at: March 22, 2026, 4:10 p.m.