Triple
T20877308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dustin Nguyen |
E514051
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | V.I.P. (TV series) |
—
|
NE NERFINISHED |
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: V.I.P. (TV series) | Statement: [Dustin Nguyen, appearedIn, V.I.P. (TV series)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: V.I.P. (TV series) Context triple: [Dustin Nguyen, appearedIn, V.I.P. (TV series)]
-
A.
V.I.P.
chosen
V.I.P. is an action-comedy television series starring Pamela Anderson as the head of a glamorous bodyguard agency in Los Angeles.
-
B.
V.I.P.
"V.I.P." is a song featured on the album "R." by R. Kelly.
-
C.
The V.I.P.s
The V.I.P.s is a 1963 British drama film set in a London airport, featuring an ensemble cast led by Richard Burton and Elizabeth Taylor and focusing on the intersecting personal crises of wealthy and powerful travelers.
-
D.
ViP
ViP is the public transport operator responsible for running tram and bus services in the German city of Potsdam.
-
E.
One VIP
One VIP is a rewards and loyalty program brand associated with Radio One, Inc., offering benefits and incentives to its members.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6767ec0819080721e2e75bd0d66 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:45 p.m.