Triple
T18281425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levchin Prize for Real-World Cryptography |
E437871
|
entity |
| Predicate | hasLaureate |
P1618
|
FINISHED |
| Object | Tanja Lange |
—
|
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: Tanja Lange | Statement: [Levchin Prize for Real-World Cryptography, hasLaureate, Tanja Lange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanja Lange Context triple: [Levchin Prize for Real-World Cryptography, hasLaureate, Tanja Lange]
-
A.
Tanja Lange
chosen
Tanja Lange is a cryptographer known for her work on elliptic-curve cryptography and contributions to practical, high-security cryptographic software.
-
B.
Anja Tschimiakin
Anja Tschimiakin was the first wife of Russian abstract art pioneer Wassily Kandinsky.
-
C.
Anja Klein
Anja Klein is a German local politician who serves as the mayor of the town of Ladenburg.
-
D.
Juliane Blasi
Juliane Blasi is an automotive designer best known for her work on BMW’s second-generation Z4 (E89) roadster.
-
E.
Michaela Reichelt
Michaela Reichelt is a German local politician who serves as the mayor of the municipality of Inning am Ammersee in Bavaria.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50056ea0481908d66bf263ac80c75 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 10:35 a.m.