Triple
T21591214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mithraism |
E532782
|
entity |
| Predicate | geographicSpread |
P2178
|
FINISHED |
| Object | Germania |
—
|
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: Germania | Statement: [Mithraism, geographicSpread, Germania]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Germania Context triple: [Mithraism, geographicSpread, Germania]
-
A.
Germania
chosen
Germania was the ancient Roman term for the vast region of central Europe inhabited by various Germanic tribes beyond the empire’s northeastern frontiers.
-
B.
Teutônia
Teutônia is a municipality in the Brazilian state of Rio Grande do Sul known for its strong German-Brazilian cultural heritage and traditions.
-
C.
Saksa
Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
-
D.
Francen
Francen is a surname most notably associated with Victor Francen, a Belgian-born actor prominent in early 20th-century European and American cinema.
-
E.
Prussia
Prussia was a historically powerful German state and kingdom that became a leading military and political force in Europe, ultimately playing a central role in the unification of Germany.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefaddc8508190950b31e2df865ad1 |
completed | April 27, 2026, 5:57 a.m. |
Created at: April 16, 2026, 6:32 p.m.