Triple
T241682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber |
E4943
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object |
Nelson Chai
Nelson Chai is a business executive and former Chief Financial Officer of Uber Technologies, known for his leadership roles in major financial and technology companies.
|
E30979
|
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: Nelson Chai | Statement: [Uber, hasKeyPerson, Nelson Chai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelson Chai Context triple: [Uber, hasKeyPerson, Nelson Chai]
-
A.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
B.
Joe Tsai
Joe Tsai is a Taiwanese-Canadian billionaire businessman and co-founder of Alibaba Group who owns the NBA’s Brooklyn Nets.
-
C.
Fang-Howard Chang
Fang-Howard Chang is an engineer and innovator recognized with the prestigious Edison Medal for his significant contributions to electrical science and technology.
-
D.
Hannibal Chau
Hannibal Chau is a flamboyant black-market dealer in kaiju organs from the film "Pacific Rim," known for his eccentric style and shady charisma.
-
E.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
- 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: Nelson Chai Triple: [Uber, hasKeyPerson, Nelson Chai]
Generated description
Nelson Chai is a business executive and former Chief Financial Officer of Uber Technologies, known for his leadership roles in major financial and technology companies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nelson Chai Target entity description: Nelson Chai is a business executive and former Chief Financial Officer of Uber Technologies, known for his leadership roles in major financial and technology companies.
-
A.
Tony Wu
Tony Wu is a member of the technical team at xAI, the artificial intelligence company founded by Elon Musk.
-
B.
Joe Tsai
Joe Tsai is a Taiwanese-Canadian billionaire businessman and co-founder of Alibaba Group who owns the NBA’s Brooklyn Nets.
-
C.
Fang-Howard Chang
Fang-Howard Chang is an engineer and innovator recognized with the prestigious Edison Medal for his significant contributions to electrical science and technology.
-
D.
Hannibal Chau
Hannibal Chau is a flamboyant black-market dealer in kaiju organs from the film "Pacific Rim," known for his eccentric style and shady charisma.
-
E.
Greg Yang
Greg Yang is a mathematician and AI researcher known for his work on the theoretical foundations of deep learning and his role at xAI.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25cee6f208190b996be4faa700910 |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36961e5688190b3a1ff61bb06233c |
completed | Feb. 28, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_69a369de04048190b2dc01cc328e644d |
completed | Feb. 28, 2026, 10:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a36a48d5a88190a727fec1c25a1d5b |
completed | Feb. 28, 2026, 10:20 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.