Triple
T20079030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Hurley |
E499946
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Andrew Hurley |
—
|
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: Andrew Hurley | Statement: [Dan Hurley, hasChild, Andrew Hurley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Hurley Context triple: [Dan Hurley, hasChild, Andrew Hurley]
-
A.
Andrew Hurley
chosen
Andrew Hurley is best known as the drummer for the American rock band Fall Out Boy.
-
B.
Michael V. Hurley
Michael V. Hurley is a notable individual recognized for achievements or public prominence associated with the surname Hurley.
-
C.
Michael T. Hurley
Michael T. Hurley is a notable individual recognized for achievements or prominence associated with the surname Hurley.
-
D.
Daniel S. Hurley
Daniel S. Hurley is an American basketball coach and former player best known for leading the University of Connecticut (UConn) men’s basketball program to national prominence.
-
E.
Michael K. Hurley
Michael K. Hurley is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Hurley.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643e216c819088c002fc1de2772a |
completed | April 20, 2026, 5:37 p.m. |
Created at: April 11, 2026, 3:40 p.m.