Triple
T19320522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermann |
E483209
|
entity |
| Predicate | nameVariant |
P744
|
FINISHED |
| Object | Germann |
—
|
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: Germann | Statement: [Hermann, nameVariant, Germann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Germann Context triple: [Hermann, nameVariant, Germann]
-
A.
Germann
chosen
Germann is a surname most notably associated with American actor Greg Germann, known for his roles in television and film.
-
B.
Alemão
Alemão is a former Brazilian midfielder best known for his influential role at Napoli in the late 1980s and early 1990s, where he helped the club achieve major European and domestic success.
-
C.
Germans
Germans are a Central European ethnic group primarily associated with Germany, characterized by the German language and a shared cultural and historical heritage.
-
D.
Saksa
Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
-
E.
Germán
Germán is a Spanish given name, commonly used in Spanish-speaking countries and derived from the same roots as the name Germain.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d87a0088190a60201b1f388089e |
completed | April 20, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:32 p.m.