Triple
T2182878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thuringia |
E49084
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Altenburg |
E296758
|
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: Altenburg | Statement: [Thuringia, containsCity, Altenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altenburg Context triple: [Thuringia, containsCity, Altenburg]
-
A.
Altenburg
chosen
Altenburg is a historic town in eastern Thuringia, Germany, known for its playing-card tradition and as the birthplace of the card game Skat.
-
B.
Kronach
Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
-
C.
Wurzen
Wurzen is a historic town in the German state of Saxony, known for its medieval architecture and location on the river Mulde east of Leipzig.
-
D.
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.
-
E.
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.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf0d551881909d7f907378e1b2b7 |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4dadd801481909551f6ed73e02fc2 |
completed | March 14, 2026, 3:49 a.m. |
Created at: March 4, 2026, 7:45 p.m.