Triple
T3374600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Bubbles |
E71036
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Ralph Sheldon
Ralph Sheldon is a film editor known for his work on the 1967 British comedy-drama "Charlie Bubbles."
|
E352305
|
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: Ralph Sheldon | Statement: [Charlie Bubbles, editedBy, Ralph Sheldon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Sheldon Context triple: [Charlie Bubbles, editedBy, Ralph Sheldon]
-
A.
Darryl Philbin
Darryl Philbin is a laid-back yet sharp-witted warehouse foreman who becomes a key supporting character and later office employee in the U.S. version of The Office.
-
B.
Marcus T. Paulk
Marcus T. Paulk is an American actor and rapper best known for his role as Myles Mitchell on the television sitcom "Moesha."
-
C.
Kevin Willard
Kevin Willard is an American college basketball coach best known for leading the University of Maryland men's basketball program after a successful tenure at Seton Hall.
-
D.
Larry Robinson
Larry Robinson is an American academic and administrator best known for serving as president of Florida A&M University.
-
E.
Larry Robinson
Larry Robinson is a Hall of Fame Canadian ice hockey defenseman best known for his long, successful career with the Montreal Canadiens and multiple Stanley Cup championships.
- 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: Ralph Sheldon Triple: [Charlie Bubbles, editedBy, Ralph Sheldon]
Generated description
Ralph Sheldon is a film editor known for his work on the 1967 British comedy-drama "Charlie Bubbles."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ralph Sheldon Target entity description: Ralph Sheldon is a film editor known for his work on the 1967 British comedy-drama "Charlie Bubbles."
-
A.
Darryl Philbin
Darryl Philbin is a laid-back yet sharp-witted warehouse foreman who becomes a key supporting character and later office employee in the U.S. version of The Office.
-
B.
Marcus T. Paulk
Marcus T. Paulk is an American actor and rapper best known for his role as Myles Mitchell on the television sitcom "Moesha."
-
C.
Kevin Willard
Kevin Willard is an American college basketball coach best known for leading the University of Maryland men's basketball program after a successful tenure at Seton Hall.
-
D.
Larry Robinson
Larry Robinson is a Hall of Fame Canadian ice hockey defenseman best known for his long, successful career with the Montreal Canadiens and multiple Stanley Cup championships.
-
E.
Larry Robinson
Larry Robinson is an American academic and administrator best known for serving as president of Florida A&M University.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bf4ad88190a2c49dc30f323a13 |
completed | March 8, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33442f28c8190b48a662a5dd1bac3 |
completed | March 12, 2026, 9:46 p.m. |
| NEDg | Description generation | batch_69b334bd2cf081908503cb4cbdfc998c |
completed | March 12, 2026, 9:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b33529b31c8190811a659df8c5d2d4 |
completed | March 12, 2026, 9:50 p.m. |
Created at: March 8, 2026, 3:13 p.m.