Triple
T14358823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Intruder (2019 film) |
E356041
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Joseph Sikora |
E1066010
|
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: Joseph Sikora | Statement: [The Intruder (2019 film), starring, Joseph Sikora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joseph Sikora Context triple: [The Intruder (2019 film), starring, Joseph Sikora]
-
A.
Joseph Sikora
chosen
Joseph Sikora is an American actor best known for playing the ruthless drug dealer Tommy Egan in the Power television franchise.
-
B.
Joe Pisarcik
Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
-
C.
Edward Kazmierczak
Edward Kazmierczak is a former Polish footballer best known for his time playing for Stal Mielec.
-
D.
Michael Socha
Michael Socha is an English actor known for his roles in television dramas and fantasy series, including prominent parts in shows like "Being Human" and "Once Upon a Time in Wonderland."
-
E.
Greg Joswiak
Greg Joswiak is a senior Apple executive who serves as the company’s Senior Vice President of Worldwide Marketing.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd550ca6b88190b76cd486bdd66fdf |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:15 a.m.