Triple
T21708332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Quigley |
E535828
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Quigley |
—
|
NE NERFINISHED |
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: Quigley | Statement: [Mike Quigley, familyName, Quigley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quigley Context triple: [Mike Quigley, familyName, Quigley]
-
A.
Quigley
chosen
Quigley is a surname most notably associated with American politician Mike Quigley, a U.S. Representative from Illinois.
-
B.
The Quigley
The Quigley is a notorious water obstacle course at the U.S. Marine Corps Officer Candidates School, known for its muddy trenches, submerged passages, and physically demanding conditions.
-
C.
Buckley
Buckley is a small city in Washington State known for its rural character and proximity to Mount Rainier.
-
D.
Buckley
Buckley is a small town in Flintshire, northeast Wales, known historically for its brickworks and coal mining industries.
-
E.
Buckley
Buckley is a surname most prominently associated with William F. Buckley Jr., the influential American conservative author and founder of National Review.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5314a288190b4b8347cca15aaa8 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:46 p.m.