Triple
T21708594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mia Sara |
E535836
|
entity |
| Predicate | hasWorkedWith |
P9615
|
FINISHED |
| Object | Alan Ruck |
—
|
NE NERFINISHED |
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: Alan Ruck | Statement: [Mia Sara, hasWorkedWith, Alan Ruck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alan Ruck Context triple: [Mia Sara, hasWorkedWith, Alan Ruck]
-
A.
Alan Ruck
chosen
Alan Ruck is an American actor best known for his roles as Cameron Frye in "Ferris Bueller's Day Off" and Connor Roy in the television series "Succession."
-
B.
Jason Miller
Jason Miller was an American actor and playwright best known for his Oscar-nominated role as Father Damien Karras in the classic horror film "The Exorcist."
-
C.
Jason Miller
Jason Miller is a software engineer best known as the creator of the lightweight JavaScript library Preact.
-
D.
Andrew McCarthy
Andrew McCarthy is an American actor and director best known as a member of the 1980s "Brat Pack," with notable roles in films like "St. Elmo's Fire," "Pretty in Pink," and "Weekend at Bernie's."
-
E.
Ed Begley
Ed Begley was an American character actor and Academy Award winner known for his prolific film, television, and stage work in the mid-20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5314a288190b4b8347cca15aaa8 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:46 p.m.