Triple
T22660856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Blackett |
E559656
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | Missee Lee |
—
|
NE NERFINISHED |
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: Missee Lee | Statement: [Peggy Blackett, appearsIn, Missee Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Missee Lee Context triple: [Peggy Blackett, appearsIn, Missee Lee]
-
A.
Missee Lee
chosen
Missee Lee is a 1941 children's adventure novel by Arthur Ransome in the Swallows and Amazons series, featuring a Chinese pirate leader and a voyage in the South China Sea.
-
B.
Honglak Lee
Honglak Lee is a computer scientist and researcher known for his contributions to deep learning and representation learning, particularly in unsupervised feature learning.
-
C.
June Woo
June Woo is the introspective Chinese American daughter and central narrator in Amy Tan’s novel *The Joy Luck Club*, whose story explores cultural identity, mother-daughter conflict, and generational trauma.
-
D.
Yun Lee
Yun Lee is the child of Korean-American actor and martial artist Will Yun Lee.
-
E.
Jin Lee
Jin Lee is the gentle, supportive father of protagonist Meilin "Mei" Lee in Pixar's animated film "Turning Red."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765edf88819086c28525e3c73758 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:07 p.m.