Triple
T22023285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blood and Water |
E543893
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Loretta Yu
Loretta Yu is an actress known for her role in the Canadian television drama series "Blood and Water."
|
E1514242
|
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: Loretta Yu | Statement: [Blood and Water, castMember, Loretta Yu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loretta Yu Context triple: [Blood and Water, castMember, Loretta Yu]
-
A.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
B.
Linda Yueh
Linda Yueh is a British economist, broadcaster, and author known for her work on global economic policy and for presenting and commenting on economic issues in the media.
-
C.
Laurel Yeung
Laurel Yeung is a central teenage character from the Canadian television drama "Edgemont," known for navigating complex friendships, family issues, and romantic relationships.
-
D.
Rita Hsiao
Rita Hsiao is a screenwriter best known for her work on animated feature films, including co-writing Pixar's "Toy Story 2."
-
E.
Yvonne Chan
Yvonne Chan is the spouse of Dennis Chan, a Hong Kong actor and film director.
- 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: Loretta Yu Triple: [Blood and Water, castMember, Loretta Yu]
Generated description
Loretta Yu is an actress known for her role in the Canadian television drama series "Blood and Water."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loretta Yu Target entity description: Loretta Yu is an actress known for her role in the Canadian television drama series "Blood and Water."
-
A.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
B.
Linda Yueh
Linda Yueh is a British economist, broadcaster, and author known for her work on global economic policy and for presenting and commenting on economic issues in the media.
-
C.
Laurel Yeung
Laurel Yeung is a central teenage character from the Canadian television drama "Edgemont," known for navigating complex friendships, family issues, and romantic relationships.
-
D.
Rita Hsiao
Rita Hsiao is a screenwriter best known for her work on animated feature films, including co-writing Pixar's "Toy Story 2."
-
E.
Yvonne Chan
Yvonne Chan is the spouse of Dennis Chan, a Hong Kong actor and film director.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c9959481908da6bed356199f75 |
completed | April 28, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a738722a88190898c5fc5f37e5b5d |
completed | May 18, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_6a0a745e534881909a681b9f2234afa5 |
completed | May 18, 2026, 2:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a7857e6dc819088b592cdff7d4cf3 |
completed | May 18, 2026, 2:24 a.m. |
Created at: April 16, 2026, 8:23 p.m.