Triple
T10068352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert N. Noyce Award |
E213154
|
entity |
| Predicate | hasAwarded |
P2391
|
FINISHED |
| Object |
Kinam Kim
Kinam Kim is a prominent South Korean semiconductor executive and technologist recognized for his leadership and contributions to the global chip industry.
|
E839049
|
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: Kinam Kim | Statement: [Robert N. Noyce Award, hasAwarded, Kinam Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinam Kim Context triple: [Robert N. Noyce Award, hasAwarded, Kinam Kim]
-
A.
Jung Kim
Jung Kim is the charismatic and quick-witted convenience store manager and son in the Canadian sitcom "Kim's Convenience."
-
B.
Jae-on Kim
Jae-on Kim is a political scientist known for his work on democratic participation and political equality.
-
C.
Nakyung Park
Nakyung Park is a South Korean painter and artist best known publicly as the wife of American actor Wesley Snipes.
-
D.
Jane Kim
Jane Kim is an American politician and attorney who served on the San Francisco Board of Supervisors and is known for her progressive advocacy on housing, education, and workers’ rights.
-
E.
Hyein Park
Hyein Park is a Korean-Canadian voice actress best known for voicing the character Abby in Pixar’s animated film "Turning Red."
- 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: Kinam Kim Triple: [Robert N. Noyce Award, hasAwarded, Kinam Kim]
Generated description
Kinam Kim is a prominent South Korean semiconductor executive and technologist recognized for his leadership and contributions to the global chip industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kinam Kim Target entity description: Kinam Kim is a prominent South Korean semiconductor executive and technologist recognized for his leadership and contributions to the global chip industry.
-
A.
Jung Kim
Jung Kim is the charismatic and quick-witted convenience store manager and son in the Canadian sitcom "Kim's Convenience."
-
B.
Jae-on Kim
Jae-on Kim is a political scientist known for his work on democratic participation and political equality.
-
C.
Nakyung Park
Nakyung Park is a South Korean painter and artist best known publicly as the wife of American actor Wesley Snipes.
-
D.
Jane Kim
Jane Kim is an American politician and attorney who served on the San Francisco Board of Supervisors and is known for her progressive advocacy on housing, education, and workers’ rights.
-
E.
Hyein Park
Hyein Park is a Korean-Canadian voice actress best known for voicing the character Abby in Pixar’s animated film "Turning Red."
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff798bc8190a84af7bedea66f0a |
completed | April 2, 2026, 2:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29a96fc888190aec7cd364a0d7fb1 |
completed | April 5, 2026, 5:23 p.m. |
| NEDg | Description generation | batch_69d29b985e308190a6ec3966e02f429c |
completed | April 5, 2026, 5:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d29c5f64c881909aa3d093422fe475 |
completed | April 5, 2026, 5:31 p.m. |
Created at: March 30, 2026, 8:58 p.m.