Triple
T10325373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyundai Ioniq 5 |
E242748
|
entity |
| Predicate | designer |
P184
|
FINISHED |
| Object |
SangYup Lee
SangYup Lee is a prominent South Korean automobile designer known for leading Hyundai’s global design direction, including acclaimed models like the Ioniq 5.
|
E855444
|
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: SangYup Lee | Statement: [Hyundai Ioniq 5, designer, SangYup Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SangYup Lee Context triple: [Hyundai Ioniq 5, designer, SangYup Lee]
-
A.
Jong Wook Kim
Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
-
B.
Eui-Sung Yi
Eui-Sung Yi is a prominent architect and urban designer known for his leadership role at the innovative architecture firm Morphosis.
-
C.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Chan-sung Jung
Chan-sung Jung, widely known as "The Korean Zombie," is a South Korean mixed martial artist recognized for his exciting fighting style and success in top MMA promotions like the UFC.
-
E.
Hong Kim
Hong Kim is a film producer known for working on the animated feature "The Nut Job."
- 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: SangYup Lee Triple: [Hyundai Ioniq 5, designer, SangYup Lee]
Generated description
SangYup Lee is a prominent South Korean automobile designer known for leading Hyundai’s global design direction, including acclaimed models like the Ioniq 5.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SangYup Lee Target entity description: SangYup Lee is a prominent South Korean automobile designer known for leading Hyundai’s global design direction, including acclaimed models like the Ioniq 5.
-
A.
Jong Wook Kim
Jong Wook Kim is a machine learning researcher known for his contributions to multimodal models, including work on the development of CLIP at OpenAI.
-
B.
Eui-Sung Yi
Eui-Sung Yi is a prominent architect and urban designer known for his leadership role at the innovative architecture firm Morphosis.
-
C.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
D.
Chan-sung Jung
Chan-sung Jung, widely known as "The Korean Zombie," is a South Korean mixed martial artist recognized for his exciting fighting style and success in top MMA promotions like the UFC.
-
E.
Hong Kim
Hong Kim is a film producer known for working on the animated feature "The Nut Job."
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7cd76348190b93562112300acfc |
completed | April 7, 2026, 10:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71da93b988190ad568b0677b5d344 |
completed | April 9, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69d731887d2081908e6b4e33d400582f |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7329189708190bbd21bd40ec029b0 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:51 a.m.