Triple
T9984016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boomtown |
E196520
|
entity |
| Predicate | starred |
P5563
|
FINISHED |
| Object | Kelly Hu |
E457327
|
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: Kelly Hu | Statement: [Boomtown, starred, Kelly Hu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelly Hu Context triple: [Boomtown, starred, Kelly Hu]
-
A.
Kelly Hu
chosen
Kelly Hu is an American actress and former beauty queen known for her roles in films and television series such as "The Scorpion King," "X2: X-Men United," and various voice-acting projects.
-
B.
Kelly Chan
Kelly Chan is a Hong Kong Cantopop singer and actress known for her popularity in the late 1990s and 2000s.
-
C.
Gui Lai
Gui Lai is the Chinese title of the 2014 drama film "Coming Home," directed by Zhang Yimou and starring Gong Li, about a family torn apart and reunited during the aftermath of China's Cultural Revolution.
-
D.
Jennifer Lien
Jennifer Lien is an American actress best known for her role as Kes on the television series "Star Trek: Voyager."
-
E.
Jean Liu
Jean Liu is a prominent Chinese business executive and technology entrepreneur best known for her leadership role in ride-hailing giant Didi Chuxing.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bdc0388190bbbd4bdc5ac3adec |
completed | April 2, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a15f2708190bdc4223d933cec0f |
completed | April 5, 2026, 1:56 p.m. |
Created at: March 30, 2026, 8:49 p.m.