Triple
T23443498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amphibia |
E565468
|
entity |
| Predicate | protagonist |
P268
|
FINISHED |
| Object | Anne Boonchuy |
—
|
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: Anne Boonchuy | Statement: [Amphibia, protagonist, Anne Boonchuy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Boonchuy Context triple: [Amphibia, protagonist, Anne Boonchuy]
-
A.
Anne Boonchuy
chosen
Anne Boonchuy is the Thai-American teenage protagonist of the animated series "Amphibia," who is magically transported to a world of talking frogs and embarks on adventures that shape her growth and friendships.
-
B.
Wendy Wu
Wendy Wu is the teenage martial-arts heroine from the Disney Channel Original Movie "Wendy Wu: Homecoming Warrior," known for battling ancient evil while juggling high school life.
-
C.
Sophie Wu
Sophie Wu is a British actress known for her roles in television series such as "The Fades" and "Fresh Meat," as well as films like "Kick-Ass."
-
D.
Roro Chu
Roro Chu is a river flowing in the region of Gangtok in the Indian state of Sikkim.
-
E.
Vivian Wu
Vivian Wu is a Chinese-American actress known for her roles in films such as "The Last Emperor," "The Joy Luck Club," and various international cinema and television productions.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64717d08190a2c25e7bbfc17a2f |
completed | April 29, 2026, 6:33 a.m. |
Created at: April 17, 2026, 5:51 p.m.