Triple
T16630310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stitcher |
E404060
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Peter deVroede
Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
|
E1242911
|
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: Peter deVroede | Statement: [Stitcher, foundedBy, Peter deVroede]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter deVroede Context triple: [Stitcher, foundedBy, Peter deVroede]
-
A.
Peter De Vries
Peter De Vries was an American novelist and humorist known for his witty, satirical fiction and contributions to The New Yorker.
-
B.
Greg de Vries
Greg de Vries is a retired Canadian professional ice hockey defenceman who played over 800 NHL games and won the Stanley Cup with the Colorado Avalanche in 2001.
-
C.
David Broekman
David Broekman was an American composer and conductor best known for his work on film scores during the early sound era of Hollywood cinema.
-
D.
Frank van der Meijden
Frank van der Meijden is a Dutch local politician who serves as the mayor of the municipality of Laarbeek in the Netherlands.
-
E.
Steven Vandeput
Steven Vandeput is a Belgian politician who has served as the mayor of Hasselt and is known for his role in national and local government.
- 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: Peter deVroede Triple: [Stitcher, foundedBy, Peter deVroede]
Generated description
Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter deVroede Target entity description: Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
-
A.
Peter De Vries
Peter De Vries was an American novelist and humorist known for his witty, satirical fiction and contributions to The New Yorker.
-
B.
Greg de Vries
Greg de Vries is a retired Canadian professional ice hockey defenceman who played over 800 NHL games and won the Stanley Cup with the Colorado Avalanche in 2001.
-
C.
David Broekman
David Broekman was an American composer and conductor best known for his work on film scores during the early sound era of Hollywood cinema.
-
D.
Frank van der Meijden
Frank van der Meijden is a Dutch local politician who serves as the mayor of the municipality of Laarbeek in the Netherlands.
-
E.
Steven Vandeput
Steven Vandeput is a Belgian politician who has served as the mayor of Hasselt and is known for his role in national and local government.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e4db5081908a6085f1bc2d65b8 |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d449f708819095f83682fa03e3bf |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d53422408190ba91624194333c13 |
completed | May 10, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d5adee908190a13bfc765e7c8f06 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:17 a.m.