Triple
T7631038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heaven & Earth |
E172758
|
entity |
| Predicate | editingBy |
P1954
|
FINISHED |
| Object | Sally Menke |
E187148
|
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: Sally Menke | Statement: [Heaven & Earth, editingBy, Sally Menke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sally Menke Context triple: [Heaven & Earth, editingBy, Sally Menke]
-
A.
Sally Menke
chosen
Sally Menke was an American film editor best known for her long-time collaboration with director Quentin Tarantino on films such as Pulp Fiction, Kill Bill, and Inglourious Basterds.
-
B.
Diane Venora
Diane Venora is an American actress known for her intense, versatile performances in film, television, and theater, including prominent roles in works like "Heat" and "Romeo + Juliet."
-
C.
Michelle Mylett
Michelle Mylett is a Canadian actress best known for playing Katy on the comedy series "Letterkenny."
-
D.
Marcia Rieke
Marcia Rieke is an American astronomer renowned for her leadership in infrared instrumentation and her key role in developing the James Webb Space Telescope.
-
E.
Jo Eisinger
Jo Eisinger was an American screenwriter best known for his dark, psychologically complex film noir scripts, including classics like "Gilda" and "Night and the City."
- 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa85c57c8190acfd33e0c890c2f9 |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7b3b7348190b3387dfee04fa51d |
completed | March 29, 2026, 6:33 a.m. |
Created at: March 27, 2026, 3:56 p.m.