Triple
T6026534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean McDonough |
E134195
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sean McDonough |
E134195
|
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: Sean McDonough | Statement: [Sean McDonough, name, Sean McDonough]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean McDonough Context triple: [Sean McDonough, name, Sean McDonough]
-
A.
Sean McDonough
chosen
Sean McDonough is an American sportscaster best known for his long career calling Major League Baseball and college sports on national television.
-
B.
Kevin O'Connor
Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
-
C.
Brian Kavanagh
Brian Kavanagh is a film editor best known for his work on notable Australian and international films, including the drama "The Devil's Playground."
-
D.
Kevin J. O'Connor
Kevin J. O'Connor is an American character actor known for his eccentric and memorable supporting roles in films such as "There Will Be Blood" and "The Mummy."
-
E.
Michael McCusker
Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560cdc308190b25ca8ecb42c4e4f |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1251413c08190b1a9639e45e198d3 |
completed | March 23, 2026, 11:33 a.m. |
Created at: March 22, 2026, 4:07 p.m.