Triple
T13860536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guy Kawasaki |
E333182
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Beth Kawasaki
Beth Kawasaki is the wife of prominent venture capitalist, author, and former Apple evangelist Guy Kawasaki.
|
E1066151
|
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: Beth Kawasaki | Statement: [Guy Kawasaki, spouse, Beth Kawasaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beth Kawasaki Context triple: [Guy Kawasaki, spouse, Beth Kawasaki]
-
A.
Kayoko Miyamoto
Kayoko Miyamoto is a Japanese woman best known as the former wife of Japan’s 56th Prime Minister, Junichiro Koizumi.
-
B.
Tao Okamoto
Tao Okamoto is a Japanese model and actress best known for her breakout film role opposite Hugh Jackman in the superhero movie "The Wolverine."
-
C.
Kelly Matsumoto
Kelly Matsumoto is a film editor known for her work on major Hollywood productions, including the science fiction blockbuster "Star Trek Beyond."
-
D.
Lisa Matsuda
Lisa Matsuda is a neuroscientist best known for identifying and characterizing the CB1 cannabinoid receptor, a key component of the endocannabinoid system in the brain.
-
E.
Kazuyo Matsui
Kazuyo Matsui is a Japanese television personality, essayist, and homemaking expert known for her appearances on lifestyle and variety programs.
- 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: Beth Kawasaki Triple: [Guy Kawasaki, spouse, Beth Kawasaki]
Generated description
Beth Kawasaki is the wife of prominent venture capitalist, author, and former Apple evangelist Guy Kawasaki.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beth Kawasaki Target entity description: Beth Kawasaki is the wife of prominent venture capitalist, author, and former Apple evangelist Guy Kawasaki.
-
A.
Kayoko Miyamoto
Kayoko Miyamoto is a Japanese woman best known as the former wife of Japan’s 56th Prime Minister, Junichiro Koizumi.
-
B.
Tao Okamoto
Tao Okamoto is a Japanese model and actress best known for her breakout film role opposite Hugh Jackman in the superhero movie "The Wolverine."
-
C.
Kelly Matsumoto
Kelly Matsumoto is a film editor known for her work on major Hollywood productions, including the science fiction blockbuster "Star Trek Beyond."
-
D.
Lisa Matsuda
Lisa Matsuda is a neuroscientist best known for identifying and characterizing the CB1 cannabinoid receptor, a key component of the endocannabinoid system in the brain.
-
E.
Kazuyo Matsui
Kazuyo Matsui is a Japanese television personality, essayist, and homemaking expert known for her appearances on lifestyle and variety programs.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02de38e48190b6ead95561031c32 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0fd3ffc8190965a730843411b80 |
completed | May 3, 2026, 9:41 p.m. |
| NEDg | Description generation | batch_69f7c1e73fb481909f89ab3c0e9fb7d0 |
completed | May 3, 2026, 9:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c3396f7c8190987079bf24ac8695 |
completed | May 3, 2026, 9:50 p.m. |
Created at: April 9, 2026, 10:14 p.m.