Triple
T3321255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Day of the Jackal |
E69799
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Cyril Cusack |
E243809
|
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: Cyril Cusack | Statement: [The Day of the Jackal, castMember, Cyril Cusack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cyril Cusack Context triple: [The Day of the Jackal, castMember, Cyril Cusack]
-
A.
Cyril Cusack
chosen
Cyril Cusack was an acclaimed Irish stage and screen actor known for his prolific career in British and Irish cinema and theatre throughout the mid-20th century.
-
B.
Barry Fitzgerald
Barry Fitzgerald was an Irish character actor best known for his prolific Hollywood career in the 1940s, including his Academy Award–winning performance in "Going My Way."
-
C.
Reggie Brown
Reggie Brown is an American entrepreneur best known as a co-founder of Snapchat, the multimedia messaging app developed by Snap Inc.
-
D.
Peter Boyle
Peter Boyle was an American character actor best known for his roles in films like "Young Frankenstein" and "Taxi Driver" and the TV series "Everybody Loves Raymond."
-
E.
Peter Boyle
Peter Boyle is a film editor known for his work on acclaimed movies such as "The Hours."
- 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb13b85208190b13aba355d5dafcf |
completed | March 8, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3250c720c81908a8a6fed9a6fd349 |
completed | March 12, 2026, 8:41 p.m. |
Created at: March 8, 2026, 3:11 p.m.