Triple
T5156360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RC6 |
E116319
|
entity |
| Predicate | designedBy |
P184
|
FINISHED |
| Object |
Ray Sidney
Ray Sidney is an American software engineer and early Google employee who later became known as a philanthropist and real estate investor.
|
E499329
|
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: Ray Sidney | Statement: [RC6, designedBy, Ray Sidney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ray Sidney Context triple: [RC6, designedBy, Ray Sidney]
-
A.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
B.
Robert Parrish
Robert Parrish was an American film editor and director, as well as a former child actor, known for his work on several classic Hollywood films.
-
C.
Ray Wise
Ray Wise is an American character actor known for his versatile roles in film and television, including memorable performances in "Twin Peaks," "RoboCop," and numerous other genre and dramatic works.
-
D.
Alan Baxter
Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous figures.
-
E.
John Phillip Law
John Phillip Law was an American film actor known for his roles in 1960s and 1970s movies, including notable performances in both comedies and cult classics.
- 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: Ray Sidney Triple: [RC6, designedBy, Ray Sidney]
Generated description
Ray Sidney is an American software engineer and early Google employee who later became known as a philanthropist and real estate investor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ray Sidney Target entity description: Ray Sidney is an American software engineer and early Google employee who later became known as a philanthropist and real estate investor.
-
A.
Michael Kane
Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
-
B.
Robert Parrish
Robert Parrish was an American film editor and director, as well as a former child actor, known for his work on several classic Hollywood films.
-
C.
Ray Wise
Ray Wise is an American character actor known for his versatile roles in film and television, including memorable performances in "Twin Peaks," "RoboCop," and numerous other genre and dramatic works.
-
D.
Alan Baxter
Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous figures.
-
E.
John Phillip Law
John Phillip Law was an American film actor known for his roles in 1960s and 1970s movies, including notable performances in both comedies and cult classics.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79019c6481909641f173c5b3769a |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed927ad5481909907c8a1764e9fd8 |
completed | March 21, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69bed9d6e1288190be0d8d83233eb3c2 |
completed | March 21, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beda5d39b88190a7314f673de2719d |
completed | March 21, 2026, 5:50 p.m. |
Created at: March 20, 2026, 1:44 p.m.