Triple
T15625425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Pilgrim vs. the World |
E375664
|
entity |
| Predicate | characterPortrayedBy |
P1507
|
FINISHED |
| Object |
Ellen Wong
Ellen Wong is a Canadian actress best known for her breakout role as Knives Chau in the film "Scott Pilgrim vs. the World."
|
E1169272
|
NE FINISHED |
How this triple was built (4 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: Ellen Wong | Statement: [Scott Pilgrim vs. the World, characterPortrayedBy, Ellen Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ellen Wong Context triple: [Scott Pilgrim vs. the World, characterPortrayedBy, Ellen Wong]
-
A.
Gloria Fong
Gloria Fong was the wife of American character actor and restaurateur Benson Fong.
-
B.
Michelle Yee
Michelle Yee is an American philanthropist and investor best known as the wife of LinkedIn co-founder Reid Hoffman.
-
C.
Edith Chao
Edith Chao was the wife of Chinese warlord and political figure Zhang Xueliang, accompanying him through his long years of house arrest and exile.
-
D.
Rosalind Chao
Rosalind Chao is an American actress best known for her roles in "The Joy Luck Club" and the "Star Trek" franchise.
-
E.
Linda Cho
Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ellen Wong Triple: [Scott Pilgrim vs. the World, characterPortrayedBy, Ellen Wong]
Generated description
Ellen Wong is a Canadian actress best known for her breakout role as Knives Chau in the film "Scott Pilgrim vs. the World."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ellen Wong Target entity description: Ellen Wong is a Canadian actress best known for her breakout role as Knives Chau in the film "Scott Pilgrim vs. the World."
-
A.
Gloria Fong
Gloria Fong was the wife of American character actor and restaurateur Benson Fong.
-
B.
Michelle Yee
Michelle Yee is an American philanthropist and investor best known as the wife of LinkedIn co-founder Reid Hoffman.
-
C.
Edith Chao
Edith Chao was the wife of Chinese warlord and political figure Zhang Xueliang, accompanying him through his long years of house arrest and exile.
-
D.
Rosalind Chao
Rosalind Chao is an American actress best known for her roles in "The Joy Luck Club" and the "Star Trek" franchise.
-
E.
Linda Cho
Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
- F. None of above. chosen
Provenance (5 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9e5e248190ae54cda1fde51efb |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff678c9d8c8190be73b6e7ed558e99 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff6883b5048190b64e4361bc89dd80 |
completed | May 9, 2026, 5:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6911a76c819088c8a86d2106b6c6 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 10, 2026, 4:14 a.m.