Triple
T20878203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claudia Kim |
E514075
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Helen Cho
Helen Cho is a brilliant geneticist and medical doctor in the Marvel Cinematic Universe who develops advanced tissue-regeneration technology used by the Avengers and their enemies.
|
E1456951
|
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: Helen Cho | Statement: [Claudia Kim, playedCharacter, Helen Cho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Cho Context triple: [Claudia Kim, playedCharacter, Helen Cho]
-
A.
Linda Cho
Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
-
B.
Helen Ahn
Helen Ahn is a member of the Ahn family, known primarily as the child of Korean-American actor Philip Ahn.
-
C.
Sandra Cho
Sandra Cho is the wife of Canadian actor Kevin Durand.
-
D.
Margaret Chung
Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
-
E.
Sandra Chung
Sandra Chung is an American linguist known for her influential work on syntax, Austronesian languages, and the interface between grammar and semantics.
- 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: Helen Cho Triple: [Claudia Kim, playedCharacter, Helen Cho]
Generated description
Helen Cho is a brilliant geneticist and medical doctor in the Marvel Cinematic Universe who develops advanced tissue-regeneration technology used by the Avengers and their enemies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helen Cho Target entity description: Helen Cho is a brilliant geneticist and medical doctor in the Marvel Cinematic Universe who develops advanced tissue-regeneration technology used by the Avengers and their enemies.
-
A.
Linda Cho
Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
-
B.
Helen Ahn
Helen Ahn is a member of the Ahn family, known primarily as the child of Korean-American actor Philip Ahn.
-
C.
Sandra Cho
Sandra Cho is the wife of Canadian actor Kevin Durand.
-
D.
Margaret Chung
Margaret Chung was a pioneering Chinese American physician and surgeon, widely regarded as the first Chinese American woman doctor in the United States and known for her influential role in supporting U.S. military personnel during World War II.
-
E.
Sandra Chung
Sandra Chung is an American linguist known for her influential work on syntax, Austronesian languages, and the interface between grammar and semantics.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6775f108190a79cd5e8c31cecf6 |
completed | April 21, 2026, 12:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918c5509c8190b2bd57c11231c6e4 |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a091a37460481908f7c01b3402deb4d |
completed | May 17, 2026, 1:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a091a8de35881909d513527b6f32e0f |
completed | May 17, 2026, 1:31 a.m. |
Created at: April 16, 2026, 12:45 p.m.