Triple
T83518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemnitz |
E1679
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Saxony |
E11465
|
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: Saxony | Statement: [Chemnitz, locatedIn, Saxony]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saxony Context triple: [Chemnitz, locatedIn, Saxony]
-
A.
Saxony
chosen
Saxony is a historic region and former kingdom in eastern Germany, known for its cultural centers like Dresden and Leipzig and its significant role in Central European history.
-
B.
Bavaria
Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
-
C.
Mecklenburg-Vorpommern
Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
-
D.
Lower Saxony
Lower Saxony is a large federal state in northwestern Germany known for its diverse landscapes, strong industrial base, and historic cities such as Hanover and Göttingen.
-
E.
Franconia
Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4ccb5081908decac81f4af01bf |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a36729974c819091d999022059c4a7 |
completed | Feb. 28, 2026, 10:07 p.m. |
Created at: Feb. 28, 2026, 2:06 a.m.