Triple
T12662038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Barbara Bach |
E302447
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Arnstadt |
E302448
|
NE FINISHED |
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: Arnstadt | Statement: [Maria Barbara Bach, residence, Arnstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnstadt Context triple: [Maria Barbara Bach, residence, Arnstadt]
-
A.
Arnstadt
chosen
Arnstadt is a historic town in Thuringia, Germany, known for its early associations with the Bach family and its well-preserved medieval architecture.
-
B.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Altenburg
Altenburg is a historic town in eastern Thuringia, Germany, known for its playing-card tradition and as the birthplace of the card game Skat.
-
E.
Saalfeld
Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617c5b888190b37d4ede139bb49e |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688819fc8190bc03a1a11f96d25f |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:19 p.m.