Triple
T3739511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DoorDash |
E79664
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Andy Fang
Andy Fang is an American entrepreneur best known as a co-founder of the food delivery company DoorDash.
|
E383938
|
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: Andy Fang | Statement: [DoorDash, foundedBy, Andy Fang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andy Fang Context triple: [DoorDash, foundedBy, Andy Fang]
-
A.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
B.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
Benson Fong
Benson Fong was an American character actor best known for his roles in mid-20th-century Hollywood films, including several entries in the Charlie Chan series.
-
E.
Daren Tang
Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
- 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: Andy Fang Triple: [DoorDash, foundedBy, Andy Fang]
Generated description
Andy Fang is an American entrepreneur best known as a co-founder of the food delivery company DoorDash.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andy Fang Target entity description: Andy Fang is an American entrepreneur best known as a co-founder of the food delivery company DoorDash.
-
A.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
B.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
Benson Fong
Benson Fong was an American character actor best known for his roles in mid-20th-century Hollywood films, including several entries in the Charlie Chan series.
-
E.
Daren Tang
Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb404b908190b6b4ee583dee3cc9 |
completed | March 8, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db23ff3c81908d19295a7ce4a39c |
completed | March 14, 2026, 3:51 a.m. |
| NEDg | Description generation | batch_69b4dbabb314819092dbd1ece83a894c |
completed | March 14, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4dc9b80f8819083074657a32798a4 |
completed | March 14, 2026, 3:57 a.m. |
Created at: March 8, 2026, 3:34 p.m.