Triple
T15127593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fennec Shand |
E361332
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Ming-Na Wen |
E343851
|
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: Ming-Na Wen | Statement: [Fennec Shand, portrayedBy, Ming-Na Wen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ming-Na Wen Context triple: [Fennec Shand, portrayedBy, Ming-Na Wen]
-
A.
Ming-Na Wen
chosen
Ming-Na Wen is a Chinese-American actress best known for her roles in projects like ER, Agents of S.H.I.E.L.D., and various Disney productions.
-
B.
Hana Mae Lee
Hana Mae Lee is an American actress, comedian, and fashion designer best known for her role as Lilly in the Pitch Perfect film series.
-
C.
Zoë Chao
Zoë Chao is an American actress and writer known for her work in film and television, including prominent roles in indie comedies and streaming series.
-
D.
Lucy Liu
Lucy Liu is an American actress and producer known for her versatile roles in film and television, including standout performances in projects like "Ally McBeal," "Kill Bill," and "Elementary."
-
E.
Stephanie Hsu
Stephanie Hsu is an American actress best known for her acclaimed, genre-bending performance as Joy/Jobu Tupaki in the film "Everything Everywhere All at Once."
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005a1b9288190954f2d92549805e5 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7f865c08190ab8fd15c14d0c06c |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:06 a.m.