Triple
T8441779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerry O’Connell |
E199365
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Jeremiah O’Connell |
E199365
|
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: Jeremiah O’Connell | Statement: [Jerry O’Connell, birthName, Jeremiah O’Connell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeremiah O’Connell Context triple: [Jerry O’Connell, birthName, Jeremiah O’Connell]
-
A.
Jeremiah O’Driscoll
Jeremiah O’Driscoll is a film editor known for his work on major feature films, including the 2020 adaptation of "The Witches."
-
B.
Jeremiah O’Driscoll
Jeremiah O’Driscoll is a film editor best known for his work on major feature films, including serving as the editor of "The Polar Express."
-
C.
Luke Doolan
Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
-
D.
Jeremiah Masoli
Jeremiah Masoli is an American football quarterback best known for his collegiate career at the University of Oregon, where he led the Ducks’ high-powered offense in the late 2000s.
-
E.
Jerry O’Connell
chosen
Jerry O’Connell is an American actor and television host known for roles in films like "Stand by Me" and series such as "Sliders" and "Crossing Jordan."
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4dc163488190a53d8696fdba94b5 |
completed | April 2, 2026, 11:06 a.m. |
Created at: March 30, 2026, 6:08 p.m.