Triple
T3430130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genesys |
E72316
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Alec Miloslavsky
Alec Miloslavsky is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
|
E372264
|
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: Alec Miloslavsky | Statement: [Genesys, foundedBy, Alec Miloslavsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alec Miloslavsky Context triple: [Genesys, foundedBy, Alec Miloslavsky]
-
A.
Mike Sokolsky
Mike Sokolsky is a co-founder of the online education platform Udacity, known for its technology-focused courses and nanodegree programs.
-
B.
Max Zaritsky
Max Zaritsky was an American labor leader and union organizer who played a key role in the early development of industrial unionism in the United States.
-
C.
Victor Rasuk
Victor Rasuk is an American actor known for roles in films like "Lords of Dogtown" and "How to Make It in America," as well as supporting parts in major franchises.
-
D.
Martin Lev
Martin Lev was a child actor best known for his role in the 1976 musical gangster film "Bugsy Malone."
-
E.
Samuel Skavronsky
Samuel Skavronsky was the father of Marta Samuilovna Skavronskaya, who later became Empress Catherine I of Russia.
- 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: Alec Miloslavsky Triple: [Genesys, foundedBy, Alec Miloslavsky]
Generated description
Alec Miloslavsky is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alec Miloslavsky Target entity description: Alec Miloslavsky is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
-
A.
Mike Sokolsky
Mike Sokolsky is a co-founder of the online education platform Udacity, known for its technology-focused courses and nanodegree programs.
-
B.
Max Zaritsky
Max Zaritsky was an American labor leader and union organizer who played a key role in the early development of industrial unionism in the United States.
-
C.
Victor Rasuk
Victor Rasuk is an American actor known for roles in films like "Lords of Dogtown" and "How to Make It in America," as well as supporting parts in major franchises.
-
D.
Martin Lev
Martin Lev was a child actor best known for his role in the 1976 musical gangster film "Bugsy Malone."
-
E.
Samuel Skavronsky
Samuel Skavronsky was the father of Marta Samuilovna Skavronskaya, who later became Empress Catherine I of Russia.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9bd61908190a7bdd01f24334fc3 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402c6e5bc819099a5148ad509b22d |
completed | March 13, 2026, 12:27 p.m. |
| NEDg | Description generation | batch_69b40335a05c8190b51414f284bd6429 |
completed | March 13, 2026, 12:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b40a6bd4888190a26989e5f6770e2c |
completed | March 13, 2026, 1 p.m. |
Created at: March 8, 2026, 3:15 p.m.