Triple
T12510381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliza Dushku |
E299060
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Eliza Patricia Dushku |
E299060
|
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: Eliza Patricia Dushku | Statement: [Eliza Dushku, fullName, Eliza Patricia Dushku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eliza Patricia Dushku Context triple: [Eliza Dushku, fullName, Eliza Patricia Dushku]
-
A.
Eliza Dushku
chosen
Eliza Dushku is an American actress best known for her roles in films like "Bring It On" and TV series such as "Buffy the Vampire Slayer" and "Dollhouse."
-
B.
Julia Faye
Julia Faye was an American actress best known for her frequent collaborations with director Cecil B. DeMille during the silent and early sound film eras.
-
C.
Sarah Miles
Sarah Miles is an English actress known for her roles in films such as "Ryan's Daughter" and "Blow-Up."
-
D.
Danielle Nicolet
Danielle Nicolet is an American actress best known for her role as Cecile Horton on the superhero television series "The Flash."
-
E.
Eve Lockhart
Eve Lockhart is a forensic pathologist character in the British crime drama series "Waking the Dead," known for her expertise in post-mortem analysis and involvement in solving cold cases.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541d6e508190a4992f328e077467 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b82189081908deb76cdd4e65245 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 8, 2026, 9:57 p.m.