Triple
T10301062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Colicos |
E241628
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Colicos |
E241628
|
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: John Colicos | Statement: [John Colicos, name, John Colicos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Colicos Context triple: [John Colicos, name, John Colicos]
-
A.
John Colicos
chosen
John Colicos was a Canadian actor best known for his powerful character roles in film and television, including iconic performances in Battlestar Galactica and Star Trek.
-
B.
Joe Corallo
Joe Corallo is a comic book writer and editor known for his work on independent and genre titles in the modern comics scene.
-
C.
John Cusimano
John Cusimano is an American lawyer, musician, and television producer best known as the longtime husband of celebrity chef and TV host Rachael Ray.
-
D.
Vince Colletta
Vince Colletta was an American comic book artist and prolific inker best known for his extensive work at Marvel Comics, particularly on titles like Thor and various Asgardian-related series.
-
E.
Frank Yaconelli
Frank Yaconelli was an Italian-American character actor and musician known for his comic supporting roles in numerous Hollywood films from the 1930s and 1940s.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4415b7f848190a9fc8b08824f0b9b |
completed | April 19, 2026, 2:43 a.m. |
Created at: April 6, 2026, 11:44 a.m.