Triple
T19623309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethan Peck |
E471068
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ethan Peck |
—
|
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: Ethan Peck | Statement: [Ethan Peck, name, Ethan Peck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ethan Peck Context triple: [Ethan Peck, name, Ethan Peck]
-
A.
Ethan Peck
chosen
Ethan Peck is an American actor best known for portraying Spock in the television series "Star Trek: Strange New Worlds."
-
B.
Ferdia Walsh-Peelo
Ferdia Walsh-Peelo is an Irish actor and musician best known for his breakout role in the film "Sing Street" and his performance in the Academy Award–winning drama "CODA."
-
C.
Madison Iseman
Madison Iseman is an American actress known for her roles in films such as the Jumanji franchise and various television series.
-
D.
Evan Alex
Evan Alex is an American child actor best known for his role in Jordan Peele’s horror film "Us."
-
E.
Jeremy Irvine
Jeremy Irvine is an English actor best known for his breakout role in Steven Spielberg’s "War Horse" and subsequent performances in films such as "The Railway Man."
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e8695c81909268c5a91cdbb7fa |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.