Triple
T16457294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knocked Up |
E399715
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Michael L. Sale |
E272646
|
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: Michael L. Sale | Statement: [Knocked Up, editedBy, Michael L. Sale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael L. Sale Context triple: [Knocked Up, editedBy, Michael L. Sale]
-
A.
Michael L. Sale
chosen
Michael L. Sale is a film editor known for his work on major Hollywood comedies, including the hit movie "Bridesmaids."
-
B.
Michael L. Sale
Michael L. Sale is an editor known for his work on the publication "Central Intelligence."
-
C.
Michael J. Weithorn
Michael J. Weithorn is an American television writer and producer best known for creating and working on several sitcoms, including "Ned and Stacey" and "The King of Queens."
-
D.
Michael W. Burns
Michael W. Burns is an actor known for his role in the Western television miniseries "Broken Trail."
-
E.
Richard P. Saller
Richard P. Saller is a historian and classical scholar known for his influential research on the social and economic structures of ancient Rome, particularly Roman family life and patriarchy.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d7dfd188190b03e9b4151a4d3d8 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f51d93081909ede0adcf8e604d4 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.