Triple
T9532831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Data General |
E229936
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Richard Sogge
Richard Sogge is an entrepreneur best known as a founder of the minicomputer company Data General.
|
E805884
|
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: Richard Sogge | Statement: [Data General, foundedBy, Richard Sogge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richard Sogge Context triple: [Data General, foundedBy, Richard Sogge]
-
A.
Michael T. Sauer
Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
-
B.
Richard C. Meyer
Richard C. Meyer was a film editor known for his work on mid-20th-century American movies, including Westerns and genre films.
-
C.
Richard Masur
Richard Masur is an American character actor known for his extensive film and television work since the 1970s, including roles in movies like "Risky Business" and the miniseries "It."
-
D.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
-
E.
Michael P. Brenner
Michael P. Brenner is an American applied mathematician and physicist known for his influential work in fluid dynamics and complex systems.
- 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: Richard Sogge Triple: [Data General, foundedBy, Richard Sogge]
Generated description
Richard Sogge is an entrepreneur best known as a founder of the minicomputer company Data General.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Richard Sogge Target entity description: Richard Sogge is an entrepreneur best known as a founder of the minicomputer company Data General.
-
A.
Michael T. Sauer
Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
-
B.
Richard C. Meyer
Richard C. Meyer was a film editor known for his work on mid-20th-century American movies, including Westerns and genre films.
-
C.
Richard Masur
Richard Masur is an American character actor known for his extensive film and television work since the 1970s, including roles in movies like "Risky Business" and the miniseries "It."
-
D.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
-
E.
Michael P. Brenner
Michael P. Brenner is an American applied mathematician and physicist known for his influential work in fluid dynamics and complex systems.
- 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_69ca8479934c81908006d0e6e970ae05 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98b5651881908241b040f123c6a8 |
completed | April 1, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c4033c08190a71535b63d86f4df |
completed | April 4, 2026, 5:37 p.m. |
| NEDg | Description generation | batch_69d14df56ac881909fad7241797b1829 |
completed | April 4, 2026, 5:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14e7a8ca88190b38c93ff312e7333 |
completed | April 4, 2026, 5:46 p.m. |
Created at: March 30, 2026, 8 p.m.