Triple
T3772935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Out of Sight |
E83237
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Karen Sisco |
E352860
|
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: Karen Sisco | Statement: [Out of Sight, character, Karen Sisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Sisco Context triple: [Out of Sight, character, Karen Sisco]
-
A.
Karen Sisco
chosen
Karen Sisco is a fictional U.S. Marshal and the protagonist of Elmore Leonard’s crime stories, best known from the film "Out of Sight" and the short-lived TV series adaptation.
-
B.
Kim Keever
Kim Keever is an American artist and photographer known for his large-scale, otherworldly landscape images created by photographing paint and materials suspended in water.
-
C.
Bonnie Owens
Bonnie Owens was an American country music singer and songwriter known for her work in the Bakersfield sound and her collaborations with Merle Haggard and Buck Owens.
-
D.
Donna Dixon
Donna Dixon is an American actress and former model known for her roles in 1980s comedies and for her long career in film and television.
-
E.
Joanne Tucker
Joanne Tucker is an American actress known for her work in independent films and theater, as well as for her involvement in arts-focused nonprofit initiatives.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc57c9e48190a0f254e47348bf32 |
completed | March 8, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e52bb2d08190b457dd517ff366d7 |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:36 p.m.