Triple
T17354211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Kerr |
E421892
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mark Kerr |
—
|
NE ONNED1 |
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: Mark Kerr | Statement: [Mark Kerr, name, Mark Kerr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Kerr Context triple: [Mark Kerr, name, Mark Kerr]
-
A.
Mark Kerr
chosen
Mark Kerr is a retired American mixed martial artist and former collegiate wrestling champion who gained prominence in the late 1990s through his dominant performances in organizations like the UFC and PRIDE.
-
B.
John Kibler
John Kibler was a longtime Major League Baseball umpire best known for serving as crew chief during the 1986 World Series.
-
C.
James Kerr
James Kerr was a 19th-century American soldier and Texas pioneer after whom the city of Kerrville, Texas, is named.
-
D.
James Kearns
James Kearns is an American screenwriter best known for writing the 2002 crime thriller film "John Q."
-
E.
Ken Ralston
Ken Ralston is an acclaimed visual effects supervisor known for his groundbreaking work on major films such as the Star Wars and Back to the Future series.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2f26548190a8822b2470ec3c72 |
completed | April 19, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01955a50dc819090c1a0ec111d9fc0 |
in_progress | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:44 a.m.