Triple
T16769745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Hochuli |
E407560
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Shawn Hochuli |
E109185
|
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: Shawn Hochuli | Statement: [Ed Hochuli, hasRelative, Shawn Hochuli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shawn Hochuli Context triple: [Ed Hochuli, hasRelative, Shawn Hochuli]
-
A.
Shawn Hochuli
chosen
Shawn Hochuli is an American NFL official who followed his father Ed Hochuli into a prominent career as a referee.
-
B.
Tully Marshall
Tully Marshall was an American character actor of the silent and early sound film era, known for his prolific work in supporting roles across numerous Hollywood productions.
-
C.
Michael Clemons
Michael Clemons is a professional gridiron football player known for his career as a defensive end in the Canadian Football League.
-
D.
Charles Joiner Jr.
Charles Joiner Jr. is better known as Charlie Joiner, a Hall of Fame former NFL wide receiver and longtime San Diego Chargers star.
-
E.
Nnamdi Asomugha
Nnamdi Asomugha is a former NFL cornerback, best known for his standout years with the Oakland Raiders and later work as a film producer and actor.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b0356a9c8190b316cd00223e7537 |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb0911488190a65c1dc536b6ea3e |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:21 a.m.