Triple
T23094970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Last Ship |
E575857
|
entity |
| Predicate | starred |
P5563
|
FINISHED |
| Object | Aaron Lazar |
—
|
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: Aaron Lazar | Statement: [The Last Ship, starred, Aaron Lazar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aaron Lazar Context triple: [The Last Ship, starred, Aaron Lazar]
-
A.
Aaron Lazar
chosen
Aaron Lazar is an American stage and screen actor best known for his work in Broadway musicals and national tours.
-
B.
Jared Bernstein
Jared Bernstein is an American economist and policy advisor who has served in prominent roles shaping U.S. economic policy, including as a key advisor in the Obama and Biden administrations.
-
C.
Aaron Berger
Aaron Berger is a film producer known for his work on the animated feature "The Book of Life."
-
D.
Stephen A. Miller
Stephen A. Miller is a writer best known for his work on the story for the horror film "My Bloody Valentine."
-
E.
Sam Weisman
Sam Weisman is an American film and television director and producer known for his work on comedies such as "George of the Jungle" and various popular TV series.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de3b2b481909ef598b447ed4dd2 |
completed | April 29, 2026, 4:49 a.m. |
Created at: April 17, 2026, 3:57 p.m.