Triple
T19602777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreuzberg (Rhön) |
E470521
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | state of Bavaria |
—
|
NE NERFINISHED |
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: state of Bavaria | Statement: [Kreuzberg (Rhön), locatedIn, state of Bavaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: state of Bavaria Context triple: [Kreuzberg (Rhön), locatedIn, state of Bavaria]
-
A.
People's State of Bavaria
The People's State of Bavaria was a short-lived socialist-leaning republic established in Bavaria in 1918–1919 following the collapse of the German Empire.
-
B.
state of Hesse
The state of Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main, extensive forests, and significant cultural and economic influence.
-
C.
Baviera
Baviera is a barangay, or local administrative village, within the city of Sagay in the Philippines.
-
D.
Bavaria
chosen
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.
-
E.
Baden-Württemberg
Baden-Württemberg is a federal state in southwest Germany known for its strong economy, automotive industry, and cities like Stuttgart, Heidelberg, and Freiburg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64080a57c8190837cbe82b93163bf |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.