Triple
T8739323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qui-Gon Jinn |
E207461
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Liam Neeson |
E34013
|
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: Liam Neeson | Statement: [Qui-Gon Jinn, voiceActor, Liam Neeson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liam Neeson Context triple: [Qui-Gon Jinn, voiceActor, Liam Neeson]
-
A.
Liam Neeson
chosen
Liam Neeson is an Irish actor renowned for his powerful performances in dramas and action films, including roles in "Schindler's List," "Taken," and "Star Wars: Episode I – The Phantom Menace."
-
B.
Sean Brosnan
Sean Brosnan is an American actor and filmmaker, best known as the son of Irish actor Pierce Brosnan.
-
C.
Paris Brosnan
Paris Brosnan is an American model and filmmaker, best known as the son of actor Pierce Brosnan and for his work in fashion and humanitarian projects.
-
D.
Stephen Lang
Stephen Lang is an American actor known for his intense character roles in film, television, and theater, including prominent performances in movies like "Avatar" and "Public Enemies."
-
E.
Bob Hoskins
Bob Hoskins was an acclaimed English actor known for his intense, often gritty performances in films such as "The Long Good Friday," "Mona Lisa," and "Who Framed Roger Rabbit."
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d486e34819094a6c6ec26c047cf |
completed | March 31, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf517c6fac8190b782c8f441635814 |
completed | April 3, 2026, 5:34 a.m. |
Created at: March 30, 2026, 6:38 p.m.