Triple
T8675288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time for Three |
E205897
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Charles Yang
Charles Yang is an American violinist known for his genre-bending performances and as a member of the crossover string trio Time for Three.
|
E750362
|
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: Charles Yang | Statement: [Time for Three, hasMember, Charles Yang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Yang Context triple: [Time for Three, hasMember, Charles Yang]
-
A.
Charles Yang
Charles Yang is a linguist and cognitive scientist known for his influential work on language acquisition and the interface between linguistics and computational modeling.
-
B.
Kenneth Hsu
Kenneth Hsu is a Swiss geologist and oceanographer known for his influential work on marine geology and the Messinian salinity crisis.
-
C.
Stephen Wang
Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
-
D.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
E.
Winston Chang
Winston Chang is a Taiwanese-American lawyer and academic, known as a son of former Republic of China President Chiang Ching-kuo and for his work in legal education in the United States.
- 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: Charles Yang Triple: [Time for Three, hasMember, Charles Yang]
Generated description
Charles Yang is an American violinist known for his genre-bending performances and as a member of the crossover string trio Time for Three.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charles Yang Target entity description: Charles Yang is an American violinist known for his genre-bending performances and as a member of the crossover string trio Time for Three.
-
A.
Charles Yang
Charles Yang is a linguist and cognitive scientist known for his influential work on language acquisition and the interface between linguistics and computational modeling.
-
B.
Kenneth Hsu
Kenneth Hsu is a Swiss geologist and oceanographer known for his influential work on marine geology and the Messinian salinity crisis.
-
C.
Stephen Wang
Stephen Wang is an entrepreneur best known as a co-founder of the film and television review aggregation website Rotten Tomatoes.
-
D.
John Cheng
John Cheng is a film producer best known for his work on the dark comedy movie "Horrible Bosses."
-
E.
Winston Chang
Winston Chang is a Taiwanese-American lawyer and academic, known as a son of former Republic of China President Chiang Ching-kuo and for his work in legal education in the United States.
- 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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc49f54dfc8190b7a61e7ed1cfcbeb |
completed | March 31, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3960ce881908f07fb9fdafcd550 |
completed | April 2, 2026, 10:54 p.m. |
| NEDg | Description generation | batch_69cef4ce80488190be5dfa7f28d0aa59 |
completed | April 2, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cef6a6b6d4819089b3dc327a05b759 |
completed | April 2, 2026, 11:07 p.m. |
Created at: March 30, 2026, 6:32 p.m.