Triple
T14123188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shooter (2007 film) |
E339953
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Eric Sears |
E339953
|
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: Eric Sears | Statement: [Shooter (2007 film), editor, Eric Sears]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Sears Context triple: [Shooter (2007 film), editor, Eric Sears]
-
A.
Eric Sears
chosen
Eric Sears is a film editor known for his work on action and thriller movies, including the 2007 film "Shooter."
-
B.
Eric A. Sears
Eric A. Sears is a film editor known for his work on the 2015 horror-comedy movie "Krampus."
-
C.
Richard Seifert
Richard Seifert was a prominent 20th-century British architect known for his influential and often controversial modernist high-rise buildings across London.
-
D.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
-
E.
Kim Sears
Kim Sears is a British artist and the wife of professional tennis player Andy Murray, known for her presence at his matches and involvement in the tennis world.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6095548881908a9e66adccca92d2 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd54fc136881908f0ff5cafa604811 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 9, 2026, 10:22 p.m.