Triple
T13061789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jitendra Malik |
E329214
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Stella Yu
Stella Yu is a computer vision and machine learning researcher known for her work in perceptual organization, image segmentation, and computational models of visual perception.
|
E1021719
|
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: Stella Yu | Statement: [Jitendra Malik, notableStudent, Stella Yu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stella Yu Context triple: [Jitendra Malik, notableStudent, Stella Yu]
-
A.
Eileen Loo
Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
-
B.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
C.
Eugenia Yuan
Eugenia Yuan is a Hong Kong–born American actress and former rhythmic gymnast known for her roles in international martial arts and drama films.
-
D.
Candice Yu
Candice Yu is a Hong Kong actress known for her work in 1970s and 1980s Cantonese cinema and television.
-
E.
ViviAnn Yee
ViviAnn Yee is an American child voice actress known for her roles in animated films and television series, including work in the Boss Baby franchise.
- 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: Stella Yu Triple: [Jitendra Malik, notableStudent, Stella Yu]
Generated description
Stella Yu is a computer vision and machine learning researcher known for her work in perceptual organization, image segmentation, and computational models of visual perception.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stella Yu Target entity description: Stella Yu is a computer vision and machine learning researcher known for her work in perceptual organization, image segmentation, and computational models of visual perception.
-
A.
Eileen Loo
Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
-
B.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
C.
Eugenia Yuan
Eugenia Yuan is a Hong Kong–born American actress and former rhythmic gymnast known for her roles in international martial arts and drama films.
-
D.
Candice Yu
Candice Yu is a Hong Kong actress known for her work in 1970s and 1980s Cantonese cinema and television.
-
E.
ViviAnn Yee
ViviAnn Yee is an American child voice actress known for her roles in animated films and television series, including work in the Boss Baby franchise.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980e7ee548190b4b18bdb1357c359 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e26e5d6881908663444bca67b01e |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e32bf5508190b4dc58971f8f64d0 |
completed | May 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e40a13c8819084daf9b77b46a181 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 9, 2026, 8:59 p.m.