Triple
T15488571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorothea Wilhelmine of Saxe-Zeitz |
E377118
|
entity |
| Predicate | house |
P1505
|
FINISHED |
| Object | Wettin |
E445492
|
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: Wettin | Statement: [Dorothea Wilhelmine of Saxe-Zeitz, house, Wettin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wettin Context triple: [Dorothea Wilhelmine of Saxe-Zeitz, house, Wettin]
-
A.
Wettin
chosen
Wettin is a small town in Saxony-Anhalt, Germany, historically significant as the ancestral seat of the influential House of Wettin.
-
B.
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.
-
C.
Schmalkalden
Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
-
D.
Rudolstadt
Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
-
E.
Kronach
Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faaca588190b0397bc2e27a522a |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c4303888190a93830ef534715ae |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 3:48 a.m.