Triple
T6954478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poker Face (TV series) |
E161206
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Stephanie Hsu |
E407107
|
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: Stephanie Hsu | Statement: [Poker Face (TV series), hasCastMember, Stephanie Hsu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephanie Hsu Context triple: [Poker Face (TV series), hasCastMember, Stephanie Hsu]
-
A.
Stephanie Hsu
chosen
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."
-
B.
Laura Harrier
Laura Harrier is an American actress and model best known for her roles in films like "Spider-Man: Homecoming" and "BlacKkKlansman."
-
C.
Ming-Na Wen
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.
-
D.
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.
-
E.
Lisa Ling
Lisa Ling is an American journalist, television presenter, and author known for her in-depth reporting and documentary work on social, cultural, and global issues.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7618afb0c8190b1545328c1cee5de |
completed | March 28, 2026, 5:05 a.m. |
Created at: March 27, 2026, 2:29 p.m.