Triple
T4382401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomberg L.P. |
E99160
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Charles Zegar
Charles Zegar is an American businessman and computer scientist best known as one of the co-founders of the financial information and media company Bloomberg L.P.
|
E442871
|
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: Charles Zegar | Statement: [Bloomberg L.P., foundedBy, Charles Zegar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Zegar Context triple: [Bloomberg L.P., foundedBy, Charles Zegar]
-
A.
John Kundla
John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
-
B.
Jeff Jagodzinski
Jeff Jagodzinski is an American football coach best known for his tenure as head coach at Boston College and his extensive experience as an offensive coach in both college football and the NFL.
-
C.
Brian Kotzur
Brian Kotzur is an American drummer best known for his work with the indie rock band Silver Jews.
-
D.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
E.
Michael Kuzak
Michael Kuzak is a central attorney character on the television legal drama "L.A. Law," known for his idealism and high-profile courtroom battles.
- 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: Charles Zegar Triple: [Bloomberg L.P., foundedBy, Charles Zegar]
Generated description
Charles Zegar is an American businessman and computer scientist best known as one of the co-founders of the financial information and media company Bloomberg L.P.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charles Zegar Target entity description: Charles Zegar is an American businessman and computer scientist best known as one of the co-founders of the financial information and media company Bloomberg L.P.
-
A.
John Kundla
John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
-
B.
Jeff Jagodzinski
Jeff Jagodzinski is an American football coach best known for his tenure as head coach at Boston College and his extensive experience as an offensive coach in both college football and the NFL.
-
C.
Brian Kotzur
Brian Kotzur is an American drummer best known for his work with the indie rock band Silver Jews.
-
D.
Mark Czyzewski
Mark Czyzewski is an editor known for his work on the film "Greyhound."
-
E.
Michael Kuzak
Michael Kuzak is a central attorney character on the television legal drama "L.A. Law," known for his idealism and high-profile courtroom battles.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352613dd481909e008a8db239a108 |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b627dd58dc819090d81177849fdc63 |
completed | March 15, 2026, 3:30 a.m. |
| NEDg | Description generation | batch_69b628fe10908190978dd0361628f54f |
completed | March 15, 2026, 3:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b629ab52c881909f7fbef6f77b5bc4 |
completed | March 15, 2026, 3:38 a.m. |
Created at: March 12, 2026, 11:18 p.m.