Triple
T11070597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Fish |
E261735
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Dustin Nguyen |
E514051
|
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: Dustin Nguyen | Statement: [Little Fish, starring, Dustin Nguyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dustin Nguyen Context triple: [Little Fish, starring, Dustin Nguyen]
-
A.
Dustin Nguyen
chosen
Dustin Nguyen is a Vietnamese-American actor best known for his role as Officer Harry Truman Ioki on the television series "21 Jump Street."
-
B.
Bao Nguyen
Bao Nguyen is a Vietnamese American filmmaker known for his acclaimed documentaries and contributions to Asian American and international cinema.
-
C.
Ellison Nguyen
Ellison Nguyen is the child of Pulitzer Prize–winning Vietnamese American author and scholar Viet Thanh Nguyen.
-
D.
David Luan
David Luan is an AI researcher and entrepreneur known for his work on large language models at OpenAI and as co-founder and CEO of Adept AI.
-
E.
Topher Ngo
Topher Ngo is a voice actor and singer best known for his role in Pixar's animated film "Turning Red."
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79922e48c81909adb161e66f47474 |
completed | April 9, 2026, 12:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c8b2d6e881909eeddf1e6427ad5c |
completed | April 18, 2026, 6:08 p.m. |
Created at: April 8, 2026, 9:26 p.m.