Triple
T3982472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoch |
E86790
|
entity |
| Predicate | refersTo |
P37
|
FINISHED |
| Object | Ed Hochuli |
E14713
|
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: Ed Hochuli | Statement: [Hoch, refersTo, Ed Hochuli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Hochuli Context triple: [Hoch, refersTo, Ed Hochuli]
-
A.
Ed Hochuli
chosen
Ed Hochuli is a former National Football League official known for his long tenure, muscular physique, and detailed on-field explanations of penalties.
-
B.
Pattie Mallette
Pattie Mallette is a Canadian author and film producer best known as the mother of pop singer Justin Bieber.
-
C.
Pam Bryant
Pam Bryant is an American woman best known as the mother of the late NBA superstar Kobe Bryant.
-
D.
Martine Bancroft
Martine Bancroft is a Marvel Comics character closely associated with the antihero Morbius, often depicted as his fiancée and a key emotional anchor in his storyline.
-
E.
Valarie Pettiford
Valarie Pettiford is an American actress, singer, and dancer known for her work on stage, television, and film, including roles in productions such as the musical "Fosse" and the TV series "Half & Half."
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9dd351c81909605bc2605f541e1 |
completed | March 9, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5561f0a2881909d758a8fba58309d |
completed | March 14, 2026, 12:35 p.m. |
Created at: March 9, 2026, 3:33 p.m.