Triple
T8709841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegiant Air |
E206746
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Dave Beadle
Dave Beadle is an entrepreneur best known as a founder of the American low-cost airline Allegiant Air.
|
E753659
|
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: Dave Beadle | Statement: [Allegiant Air, foundedBy, Dave Beadle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dave Beadle Context triple: [Allegiant Air, foundedBy, Dave Beadle]
-
A.
Tim Besse
Tim Besse is an American entrepreneur best known as a co-founder of the employee review and job-listing platform Glassdoor.
-
B.
Stuart Beattie
Stuart Beattie is an Australian screenwriter and director known for his work on major films such as "Collateral," "Pirates of the Caribbean: The Curse of the Black Pearl," and "Australia."
-
C.
Mike Beedle
Mike Beedle was a software engineer, author, and early proponent of agile and Scrum methodologies who helped popularize agile software development practices worldwide.
-
D.
Ted Bessell
Ted Bessell was an American television and film actor best known for co-starring as Donald Hollinger on the 1960s sitcom "That Girl."
-
E.
Matt Beard
Matt Beard is an English football manager known for coaching top women’s clubs, including a stint in the National Women's Soccer League with the Boston Breakers.
- 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: Dave Beadle Triple: [Allegiant Air, foundedBy, Dave Beadle]
Generated description
Dave Beadle is an entrepreneur best known as a founder of the American low-cost airline Allegiant Air.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dave Beadle Target entity description: Dave Beadle is an entrepreneur best known as a founder of the American low-cost airline Allegiant Air.
-
A.
Tim Besse
Tim Besse is an American entrepreneur best known as a co-founder of the employee review and job-listing platform Glassdoor.
-
B.
Stuart Beattie
Stuart Beattie is an Australian screenwriter and director known for his work on major films such as "Collateral," "Pirates of the Caribbean: The Curse of the Black Pearl," and "Australia."
-
C.
Mike Beedle
Mike Beedle was a software engineer, author, and early proponent of agile and Scrum methodologies who helped popularize agile software development practices worldwide.
-
D.
Ted Bessell
Ted Bessell was an American television and film actor best known for co-starring as Donald Hollinger on the 1960s sitcom "That Girl."
-
E.
Matt Beard
Matt Beard is an English football manager known for coaching top women’s clubs, including a stint in the National Women's Soccer League with the Boston Breakers.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c3034708190b895eaf890d62198 |
completed | March 31, 2026, 11:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28c174008190bc2d43ca613e9a9e |
completed | April 3, 2026, 2:41 a.m. |
| NEDg | Description generation | batch_69cf2bd14c3c8190b43840ee57cca22c |
completed | April 3, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf2cb3c4308190971fb3d25064f205 |
completed | April 3, 2026, 2:57 a.m. |
Created at: March 30, 2026, 6:35 p.m.