Triple
T21652780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Banacek |
E534379
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Banacek |
—
|
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: Banacek | Statement: [Thomas Banacek, familyName, Banacek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Banacek Context triple: [Thomas Banacek, familyName, Banacek]
-
A.
Banacek
chosen
Banacek is a 1970s American television mystery series featuring George Peppard as a suave, Polish-American insurance investigator who solves seemingly impossible thefts.
-
B.
Evilenko
Evilenko is a 2004 psychological horror-thriller film loosely inspired by the crimes of Soviet serial killer Andrei Chikatilo.
-
C.
Brunonek
Brunonek is a Polish diminutive form of the male given name Brunon, typically used as an affectionate or familiar nickname.
-
D.
Brodeck
Brodeck is the protagonist of Philippe Claudel’s novel *Le Rapport de Brodeck*, a traumatized survivor in a remote village who is tasked with writing an official report about a mysterious and violent event.
-
E.
Robert Barrat
Robert Barrat was an American character actor known for his supporting roles in numerous Hollywood films from the 1930s through the 1950s.
- 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.