Triple
T10190364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MU |
E238015
|
entity |
| Predicate | chancellor |
P325
|
FINISHED |
| Object | Mun Choi |
E847428
|
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: Mun Choi | Statement: [MU, chancellor, Mun Choi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mun Choi Context triple: [MU, chancellor, Mun Choi]
-
A.
Mun Choi
chosen
Mun Choi is a Korean-American engineer and academic administrator who serves as a prominent university leader in the United States.
-
B.
Ming Lee
Ming Lee is the strict yet loving mother of protagonist Meilin in Pixar's animated film "Turning Red," whose own emotional struggles and family legacy drive much of the story's conflict and heart.
-
C.
Wai Ching Ho
Wai Ching Ho is a Chinese-American actress known for her character roles in film and television, including work in major Hollywood productions and voice acting in animated features.
-
D.
Ling Woo
Ling Woo is a sharp-tongued, unapologetically confident attorney on the television series "Ally McBeal," known for her icy demeanor, wit, and complex relationship dynamics.
-
E.
Ka Ho Cho
Ka Ho Cho is best known as the fourth and final wife of American comedian and actor Redd Foxx.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32ae3fe40819093080f9bf15a9608 |
completed | April 6, 2026, 3:39 a.m. |
Created at: March 30, 2026, 9:13 p.m.