Triple
T3982494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Hochuli |
E86790
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object |
Ed Hoch
Ed Hoch is a retired American NFL referee renowned for his muscular physique, detailed penalty explanations, and long tenure officiating high-profile games.
|
E498956
|
NE FINISHED |
How this triple was built (4 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 Hoch | Statement: [Ed Hochuli, knownAs, Ed Hoch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Hoch Context triple: [Ed Hochuli, knownAs, Ed Hoch]
-
A.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
B.
Ed Heinemann
Ed Heinemann was a renowned American aeronautical engineer best known for designing innovative and influential military aircraft for Douglas Aircraft Company during the mid-20th century.
-
C.
Robert Hohman
Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
-
D.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
E.
Karl Schaefer
Karl Schaefer is a television writer and producer best known for co-creating the zombie apocalypse series Z Nation and its Netflix prequel Black Summer.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ed Hoch Triple: [Ed Hochuli, knownAs, Ed Hoch]
Generated description
Ed Hoch is a retired American NFL referee renowned for his muscular physique, detailed penalty explanations, and long tenure officiating high-profile games.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ed Hoch Target entity description: Ed Hoch is a retired American NFL referee renowned for his muscular physique, detailed penalty explanations, and long tenure officiating high-profile games.
-
A.
Fred Schuler
Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
-
B.
Ed Heinemann
Ed Heinemann was a renowned American aeronautical engineer best known for designing innovative and influential military aircraft for Douglas Aircraft Company during the mid-20th century.
-
C.
Robert Hohman
Robert Hohman is an American entrepreneur best known as the co-founder and former CEO of Glassdoor, a popular platform for anonymous employee reviews and salary information.
-
D.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
E.
Karl Schaefer
Karl Schaefer is a television writer and producer best known for co-creating the zombie apocalypse series Z Nation and its Netflix prequel Black Summer.
- F. None of above. chosen
Provenance (5 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_69bed8f8a8a08190b403b8c3caf20009 |
completed | March 21, 2026, 5:44 p.m. |
| NEDg | Description generation | batch_69bed9c4bd98819089c9d656379a959d |
completed | March 21, 2026, 5:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beda1519348190a09e01ce4464bccc |
completed | March 21, 2026, 5:49 p.m. |
Created at: March 9, 2026, 3:33 p.m.