Triple
T1499745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altera |
E29768
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Michael Magranet
Michael Magranet is an entrepreneur best known as a founder of the technology company Altera.
|
E176104
|
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: Michael Magranet | Statement: [Altera, foundedBy, Michael Magranet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Magranet Context triple: [Altera, foundedBy, Michael Magranet]
-
A.
Dan Iassogna
Dan Iassogna is a veteran Major League Baseball umpire who has officiated numerous postseason games, including serving as crew chief in the World Series.
-
B.
Dante Spinotti
Dante Spinotti is an acclaimed Italian cinematographer known for his visually distinctive work on films such as Heat, L.A. Confidential, and The Insider.
-
C.
Jack Mara
Jack Mara is a co-owner of the New York Giants NFL franchise and a member of the Mara family, long associated with the team's ownership and management.
-
D.
Matthias Bartoli
Matthias Bartoli is a linguist known for his work documenting and studying the now-extinct Dalmatian language.
-
E.
Chris Brancato
Chris Brancato is an American television writer and producer best known for his work on crime dramas, including co-creating the acclaimed Netflix series "Narcos."
- 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: Michael Magranet Triple: [Altera, foundedBy, Michael Magranet]
Generated description
Michael Magranet is an entrepreneur best known as a founder of the technology company Altera.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Magranet Target entity description: Michael Magranet is an entrepreneur best known as a founder of the technology company Altera.
-
A.
Dan Iassogna
Dan Iassogna is a veteran Major League Baseball umpire who has officiated numerous postseason games, including serving as crew chief in the World Series.
-
B.
Dante Spinotti
Dante Spinotti is an acclaimed Italian cinematographer known for his visually distinctive work on films such as Heat, L.A. Confidential, and The Insider.
-
C.
Jack Mara
Jack Mara is a co-owner of the New York Giants NFL franchise and a member of the Mara family, long associated with the team's ownership and management.
-
D.
Matthias Bartoli
Matthias Bartoli is a linguist known for his work documenting and studying the now-extinct Dalmatian language.
-
E.
Chris Brancato
Chris Brancato is an American television writer and producer best known for his work on crime dramas, including co-creating the acclaimed Netflix series "Narcos."
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6f0ce988190aafab4a6e0dfd710 |
completed | March 1, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad308bf1048190bc15a712e5ee0caa |
completed | March 8, 2026, 8:17 a.m. |
| NEDg | Description generation | batch_69ad3234bc508190a86647325df1d41a |
completed | March 8, 2026, 8:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad32ca046c81908bcdc3f76e65e4d0 |
completed | March 8, 2026, 8:26 a.m. |
Created at: March 1, 2026, 8:12 p.m.