Triple
T9247216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cao Cao |
E222226
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Lady Bian |
E704536
|
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: Lady Bian | Statement: [Cao Cao, spouse, Lady Bian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lady Bian Context triple: [Cao Cao, spouse, Lady Bian]
-
A.
Lady Bian
chosen
Lady Bian was an influential noblewoman of the late Eastern Han and Three Kingdoms period, best known as the wife of warlord Cao Cao and the mother of Cao Pi, the first emperor of the state of Cao Wei.
-
B.
Lady Gan
Lady Gan was the principal wife of the famed Chinese general Guan Yu during the late Eastern Han dynasty and Three Kingdoms period.
-
C.
Lady Gan
Lady Gan was a consort of Liu Bei and the mother of Shu Han’s second emperor, Liu Shan, during the Three Kingdoms period of Chinese history.
-
D.
Bianca de Passe
Bianca de Passe is a character in the romantic comedy film "Bell, Book and Candle," depicted as a member of the modern-day witch community in New York City.
-
E.
Lady Larken
Lady Larken is a romantic, high-strung noblewoman in the musical comedy "Once Upon a Mattress," whose secret pregnancy drives much of the plot’s urgency and humor.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f55a848190a59e7087cc07f6ef |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077f79cfc81908bae290aa25cf2a1 |
completed | April 4, 2026, 2:31 a.m. |
Created at: March 30, 2026, 7:31 p.m.