Triple
T16177127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Kwan |
E392592
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Nancy Kwan |
E392592
|
NE FINISHED |
How this triple was built (2 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: Nancy Kwan | Statement: [Nancy Kwan, name, Nancy Kwan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nancy Kwan Context triple: [Nancy Kwan, name, Nancy Kwan]
-
A.
Nancy Kwan
chosen
Nancy Kwan is a pioneering Hong Kong–born actress who became an international star in the 1960s and a trailblazer for Asian representation in Hollywood and global cinema.
-
B.
Estella Kwan
Estella Kwan is the mother of American figure skating champion Michelle Wingshan Kwan.
-
C.
Rita Hsiao
Rita Hsiao is a screenwriter best known for her work on animated feature films, including co-writing Pixar's "Toy Story 2."
-
D.
Vicki Wong
Vicki Wong is an author and illustrator best known for creating the popular children's book series that inspired the animated television show "The Octonauts."
-
E.
Fay Chung
Fay Chung is a Zimbabwean educator and former government minister known for her influential role in shaping post-independence education policy in Zimbabwe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e22059e7048190b4592cb1516b5f8d |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000787d3fc8190a32d53a177fedb6d |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:02 a.m.