Triple
T3287685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unser |
E69021
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Dayton Callie |
E69022
|
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: Dayton Callie | Statement: [Unser, portrayedBy, Dayton Callie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dayton Callie Context triple: [Unser, portrayedBy, Dayton Callie]
-
A.
Dayton Callie
chosen
Dayton Callie is an American actor best known for his gritty character roles on television, including prominent parts in series like Sons of Anarchy and Deadwood.
-
B.
Blaine
Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
-
C.
Daylin Mitchell
Daylin Mitchell is a South African politician who serves as the Speaker of the Western Cape Provincial Parliament.
-
D.
Dill Harris
Dill Harris is a curious and imaginative friend of Scout and Jem Finch in Harper Lee's novel "To Kill a Mockingbird," symbolizing childhood innocence and fascination with the mysterious Boo Radley.
-
E.
Addison
Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb058e00881908fdf0a23208860d4 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e85f71508190b194b4d383d7ee32 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:10 p.m.