Triple
T20397141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bela Lugosi |
E500236
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Hope Lininger |
—
|
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: Hope Lininger | Statement: [Bela Lugosi, spouse, Hope Lininger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hope Lininger Context triple: [Bela Lugosi, spouse, Hope Lininger]
-
A.
Hope Lininger
chosen
Hope Lininger was the fourth and final wife of classic horror film actor Bela Lugosi.
-
B.
Rachel Line Mellinger
Rachel Line Mellinger was the wife of James R. Schlesinger, the former U.S. Secretary of Defense and CIA Director.
-
C.
Lily Stumpf
Lily Stumpf was the wife of Swiss-German painter Paul Klee and a trained pianist who supported and influenced his artistic career.
-
D.
Lauren Hartke
Lauren Hartke is the introspective performance artist protagonist of Don DeLillo’s novel "The Body Artist," known for her intense exploration of time, identity, and the body.
-
E.
Lindsey Haun
Lindsey Haun is an American actress and singer best known for her work in film and television, including prominent roles in Disney Channel productions and the HBO series "True Blood."
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6798b6640819085d5b12dc35633fe |
completed | April 20, 2026, 7:07 p.m. |
Created at: April 16, 2026, 11:28 a.m.