Triple
T9029150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WorldCom, Inc. |
E216124
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Murray Waldron
Murray Waldron is a businessman best known as one of the founders of the telecommunications company WorldCom, Inc.
|
E823062
|
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: Murray Waldron | Statement: [WorldCom, Inc., foundedBy, Murray Waldron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murray Waldron Context triple: [WorldCom, Inc., foundedBy, Murray Waldron]
-
A.
Jack L. Murray
Jack L. Murray is a film producer best known for his work on the 2009 horror remake "My Bloody Valentine 3D."
-
B.
Murray Ward
Murray Ward is a local administrative division within the city of Quinte West in Ontario, Canada.
-
C.
Murray Franklin
Murray Franklin is a fictional late-night talk show host portrayed by Robert De Niro in the 2019 film "Joker," serving as a symbol of media cynicism and a catalyst in Arthur Fleck's transformation.
-
D.
Paul Kirkwood
Paul Kirkwood is the central protagonist of the film "Beautiful Girls," around whom the story’s themes of friendship, nostalgia, and romantic uncertainty revolve.
-
E.
Wilfred J. McNeil
Wilfred J. McNeil was an American government official who served in senior defense-related administrative roles, including leadership of the U.S. Munitions Board during the mid-20th century.
- 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: Murray Waldron Triple: [WorldCom, Inc., foundedBy, Murray Waldron]
Generated description
Murray Waldron is a businessman best known as one of the founders of the telecommunications company WorldCom, Inc.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Murray Waldron Target entity description: Murray Waldron is a businessman best known as one of the founders of the telecommunications company WorldCom, Inc.
-
A.
Jack L. Murray
Jack L. Murray is a film producer best known for his work on the 2009 horror remake "My Bloody Valentine 3D."
-
B.
Murray Ward
Murray Ward is a local administrative division within the city of Quinte West in Ontario, Canada.
-
C.
Murray Franklin
Murray Franklin is a fictional late-night talk show host portrayed by Robert De Niro in the 2019 film "Joker," serving as a symbol of media cynicism and a catalyst in Arthur Fleck's transformation.
-
D.
Paul Kirkwood
Paul Kirkwood is the central protagonist of the film "Beautiful Girls," around whom the story’s themes of friendship, nostalgia, and romantic uncertainty revolve.
-
E.
Wilfred J. McNeil
Wilfred J. McNeil was an American government official who served in senior defense-related administrative roles, including leadership of the U.S. Munitions Board during the mid-20th century.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9bcb508190b58751f1772407d4 |
completed | April 1, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc2ca7a081908f597e9a58920d6e |
completed | April 5, 2026, 2:42 a.m. |
| NEDg | Description generation | batch_69d1ccb043008190a3af47b234520891 |
completed | April 5, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1cd04694881909ab19cb4c11fbd20 |
completed | April 5, 2026, 2:46 a.m. |
Created at: March 30, 2026, 7:08 p.m.