Triple
T12662046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Barbara Bach |
E302447
|
entity |
| Predicate | marriagePlace |
P128
|
FINISHED |
| Object | Dornheim |
E306207
|
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: Dornheim | Statement: [Maria Barbara Bach, marriagePlace, Dornheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dornheim Context triple: [Maria Barbara Bach, marriagePlace, Dornheim]
-
A.
Dornheim
chosen
Dornheim is a small village in Thuringia, Germany, historically noted as the place where Johann Sebastian Bach married Maria Barbara Bach.
-
B.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
C.
Wehringen
Wehringen is a small municipality in Bavaria, Germany, situated in the region surrounding the city of Augsburg.
-
D.
Uerdingen
Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
-
E.
Badenweiler
Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
- 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_69fbac73848481909303e833041ebc90 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 5:19 p.m.