Triple
T18205130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swin Transformer |
E435882
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object |
Stephen Lin
Stephen Lin is a computer vision researcher known for his influential work in deep learning and visual recognition, including co-authoring the Swin Transformer architecture.
|
E1312474
|
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: Stephen Lin | Statement: [Swin Transformer, coAuthor, Stephen Lin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Lin Context triple: [Swin Transformer, coAuthor, Stephen Lin]
-
A.
Eric Lin
Eric Lin is a cinematographer known for his work on the drama film "I Smile Back" and other independent and feature film projects.
-
B.
Stephen Shing
Stephen Shing is a composer and musician best known for creating the musical score for the Hong Kong action-comedy film "Dragons Forever."
-
C.
Kenneth Lin
Kenneth Lin is an entrepreneur best known as the founder and former CEO of the personal finance company Credit Karma.
-
D.
Ian Chen
Ian Chen is a Taiwanese-American child actor best known for his roles in the TV series "Fresh Off the Boat" and the superhero film "Shazam!".
-
E.
Stephen Wang
Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
- 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: Stephen Lin Triple: [Swin Transformer, coAuthor, Stephen Lin]
Generated description
Stephen Lin is a computer vision researcher known for his influential work in deep learning and visual recognition, including co-authoring the Swin Transformer architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stephen Lin Target entity description: Stephen Lin is a computer vision researcher known for his influential work in deep learning and visual recognition, including co-authoring the Swin Transformer architecture.
-
A.
Eric Lin
Eric Lin is a cinematographer known for his work on the drama film "I Smile Back" and other independent and feature film projects.
-
B.
Stephen Shing
Stephen Shing is a composer and musician best known for creating the musical score for the Hong Kong action-comedy film "Dragons Forever."
-
C.
Kenneth Lin
Kenneth Lin is an entrepreneur best known as the founder and former CEO of the personal finance company Credit Karma.
-
D.
Ian Chen
Ian Chen is a Taiwanese-American child actor best known for his roles in the TV series "Fresh Off the Boat" and the superhero film "Shazam!".
-
E.
Stephen Wang
Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a039f0e52108190913cc5c667619d89 |
completed | May 12, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_6a039fdd9c4c819083b450657d0ece43 |
completed | May 12, 2026, 9:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03a0d6de8c8190b1f94c7de0856143 |
completed | May 12, 2026, 9:51 p.m. |
Created at: April 10, 2026, 10:32 a.m.