Triple
T13072321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shampoo Press & Curl |
E329485
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Jonathan Yip |
E827297
|
NE FINISHED |
How this triple was built (2 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: Jonathan Yip | Statement: [Shampoo Press & Curl, hasMember, Jonathan Yip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Yip Context triple: [Shampoo Press & Curl, hasMember, Jonathan Yip]
-
A.
Jonathan Yip
chosen
Jonathan Yip is an American songwriter and producer best known as a member of the Grammy-winning production team The Stereotypes, recognized for crafting hit songs for major pop and R&B artists.
-
B.
Brandon Yip
Brandon Yip is a Canadian professional ice hockey forward who has played in the NHL and various international leagues.
-
C.
Jason Wong
Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
-
D.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d981160e388190bab942a2ded2903e |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27058dc8190a64e1a929f296619 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 9 p.m.