Triple
T16003918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phresh Out the Runway |
E388161
|
entity |
| Predicate | mixer |
P30367
|
FINISHED |
| Object | Phil Tan |
E389666
|
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: Phil Tan | Statement: [Phresh Out the Runway, mixer, Phil Tan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Tan Context triple: [Phresh Out the Runway, mixer, Phil Tan]
-
A.
Phil Tan
chosen
Phil Tan is a Grammy-winning mixing engineer renowned for his work on numerous chart-topping pop and R&B records.
-
B.
Charles C. Tan
Charles C. Tan was a notable benefactor and alumnus of the University of California, Berkeley, for whom the university’s chemical engineering building, Tan Hall, is named.
-
C.
Daren Tang
Daren Tang is a Singaporean lawyer and intellectual property expert who serves as the Director General of the World Intellectual Property Organization (WIPO).
-
D.
Ken Kao
Ken Kao is an American film producer known for backing a range of independent and auteur-driven projects.
-
E.
Cliff Chiang
Cliff Chiang is an American comic book artist best known for co-creating and illustrating the sci-fi comic series "Paper Girls" and his acclaimed work at DC Comics, including runs on "Wonder Woman."
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157fe776c81908f7bf29ef064a6ba |
completed | April 16, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3dec0c0819099b9007ad0fc6fb4 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:55 a.m.