Triple
T21652601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Peppard |
E534374
|
entity |
| Predicate | portrayedCharacter |
P1668
|
FINISHED |
| Object | Paul Varjak |
—
|
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: Paul Varjak | Statement: [George Peppard, portrayedCharacter, Paul Varjak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Varjak Context triple: [George Peppard, portrayedCharacter, Paul Varjak]
-
A.
Paul Varjak
chosen
Paul Varjak is a struggling writer and Holly Golightly’s neighbor and love interest in Truman Capote’s novella and the film adaptation "Breakfast at Tiffany’s."
-
B.
Edward Vajda
Edward Vajda is a linguist known for proposing the Dené–Yeniseian language family hypothesis linking North American Na-Dené languages with Siberia’s Yeniseian languages.
-
C.
Samuel Pisar
Samuel Pisar was a Polish-born Holocaust survivor, international lawyer, and author known for his influential work in human rights and international economic law.
-
D.
Branko Lustig
Branko Lustig was a Croatian film producer and Holocaust survivor best known for his Academy Award–winning work on major historical epics such as Schindler’s List and Gladiator.
-
E.
Daniel Zaidenstadt
Daniel Zaidenstadt is a professional audio engineer known for his work as an assistant engineer on major hip-hop and pop recordings.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.