Triple
T748748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orlando Magic |
E15399
|
entity |
| Predicate | president |
P8
|
FINISHED |
| Object |
Jeff Weltman
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
|
E136958
|
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: Jeff Weltman | Statement: [Orlando Magic, president, Jeff Weltman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Weltman Context triple: [Orlando Magic, president, Jeff Weltman]
-
A.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
B.
Eric Friedman
Eric Friedman is an American entrepreneur best known as the co-founder and chief technology officer of the wearable fitness technology company Fitbit.
-
C.
Jon Rubinstein
Jon Rubinstein is an American computer engineer and executive best known for his key role in developing Apple's iPod and later leading Palm as CEO.
-
D.
Phillip Berman
Phillip Berman is a writer best known for coauthoring the spiritual and philosophical work "Reason for Hope: A Spiritual Journey" with primatologist Jane Goodall.
-
E.
Andy Horwitz
Andy Horwitz is a film producer best known for his work on major action and thriller projects in Hollywood.
- 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: Jeff Weltman Triple: [Orlando Magic, president, Jeff Weltman]
Generated description
Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jeff Weltman Target entity description: Jeff Weltman is a basketball executive who serves as the top front-office decision-maker for the NBA’s Orlando Magic.
-
A.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
B.
Eric Friedman
Eric Friedman is an American entrepreneur best known as the co-founder and chief technology officer of the wearable fitness technology company Fitbit.
-
C.
Jon Rubinstein
Jon Rubinstein is an American computer engineer and executive best known for his key role in developing Apple's iPod and later leading Palm as CEO.
-
D.
Phillip Berman
Phillip Berman is a writer best known for coauthoring the spiritual and philosophical work "Reason for Hope: A Spiritual Journey" with primatologist Jane Goodall.
-
E.
Andy Horwitz
Andy Horwitz is a film producer best known for his work on major action and thriller projects in Hollywood.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac762a53b48190a4d98b0416b4697c |
completed | March 7, 2026, 7:02 p.m. |
| NEDg | Description generation | batch_69ac781ccf088190a32e313fbdec711f |
completed | March 7, 2026, 7:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac78b7eb4081908167456f8e461bcb |
completed | March 7, 2026, 7:12 p.m. |
Created at: March 1, 2026, 7:37 p.m.