Triple
T17862558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frau Farbissina |
E446109
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | James Bond villains |
—
|
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: James Bond villains | Statement: [Frau Farbissina, basedOn, James Bond villains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Bond villains Context triple: [Frau Farbissina, basedOn, James Bond villains]
-
A.
James Bond
James Bond is a fictional British secret agent, code-named 007, known for his espionage missions, suave demeanor, and presence in a long-running series of novels and films.
-
B.
Jimmy Bond
Jimmy Bond is an American jazz double bassist known for his session work in the 1950s and 1960s with prominent artists such as Chet Baker and Nina Simone.
-
C.
James Bond universe
chosen
The James Bond universe is the fictional world encompassing the espionage adventures, characters, and settings surrounding British secret agent 007 across novels and films.
-
D.
Jaws (James Bond character)
Jaws is a towering, steel-toothed henchman and iconic villain-turned-antihero from the James Bond film series.
-
E.
JC Bond
JC Bond is a film editor known for working on the movie "Big Eyes."
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e49790ea148190b7a966812d44f430 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 10:17 a.m.