Triple
T19717633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Kuen Kao |
E473519
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Gwen May-Wan Kao |
E112655
|
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: Gwen May-Wan Kao | Statement: [Charles Kuen Kao, spouse, Gwen May-Wan Kao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwen May-Wan Kao Context triple: [Charles Kuen Kao, spouse, Gwen May-Wan Kao]
-
A.
Gwen May-Wan Kao
chosen
Gwen May-Wan Kao is best known as the wife and long-time partner of Nobel Prize–winning physicist Charles K. Kao, often recognized for supporting his pioneering work in fiber-optic communications.
-
B.
Karen Kwan
Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
-
C.
Mimi Wong
Mimi Wong is best known as the wife of the late Yong Pung How, who served as Chief Justice of Singapore.
-
D.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
-
E.
Michelle Wong
Michelle Wong is an actress known for her voice role in the animated feature film "Abominable."
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440ec9e881909b75c0ebefab827f |
completed | April 20, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07aba36954819085e53a67388086ab |
completed | May 15, 2026, 11:26 p.m. |
Created at: April 10, 2026, 1:46 p.m.