Triple
T20273557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chu |
E502951
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object |
Kathy Chu
Kathy Chu is a journalist known for her reporting on business, finance, and consumer issues for major news outlets.
|
E1422223
|
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: Kathy Chu | Statement: [Chu, notableBearer, Kathy Chu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathy Chu Context triple: [Chu, notableBearer, Kathy Chu]
-
A.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
B.
Melissa Chiu
Melissa Chiu is an Australian-born art historian and curator known for her leadership roles in major contemporary art institutions, including directing the Hirshhorn Museum and Sculpture Garden in Washington, D.C.
-
C.
Amy Chiang
Amy Chiang is a member of Taiwan’s influential Chiang family, known primarily as a daughter of former President Chiang Ching-kuo.
-
D.
Karin Anna Cheung
Karin Anna Cheung is an American actress and artist best known for her role in the indie film "Better Luck Tomorrow" and for her work in Asian American cinema.
-
E.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
- 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: Kathy Chu Triple: [Chu, notableBearer, Kathy Chu]
Generated description
Kathy Chu is a journalist known for her reporting on business, finance, and consumer issues for major news outlets.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kathy Chu Target entity description: Kathy Chu is a journalist known for her reporting on business, finance, and consumer issues for major news outlets.
-
A.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
B.
Melissa Chiu
Melissa Chiu is an Australian-born art historian and curator known for her leadership roles in major contemporary art institutions, including directing the Hirshhorn Museum and Sculpture Garden in Washington, D.C.
-
C.
Amy Chiang
Amy Chiang is a member of Taiwan’s influential Chiang family, known primarily as a daughter of former President Chiang Ching-kuo.
-
D.
Karin Anna Cheung
Karin Anna Cheung is an American actress and artist best known for her role in the indie film "Better Luck Tomorrow" and for her work in Asian American cinema.
-
E.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e104f081909d17c1963a5db528 |
completed | April 20, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a085a1eeed881909fdda6e5e044216e |
completed | May 16, 2026, 11:50 a.m. |
| NEDg | Description generation | batch_6a085ac5b5f4819083c4d12e9cabc758 |
completed | May 16, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a085bc0781c81909fc53a83291badc0 |
completed | May 16, 2026, 11:57 a.m. |
Created at: April 16, 2026, 10:28 a.m.