Triple
T8200674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linn |
E191563
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Nordrhein-Westfalen |
E20221
|
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: Nordrhein-Westfalen | Statement: [Linn, locatedIn, Nordrhein-Westfalen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nordrhein-Westfalen Context triple: [Linn, locatedIn, Nordrhein-Westfalen]
-
A.
North Rhine-Westphalia
chosen
North Rhine-Westphalia is Germany’s most populous federal state, known for its major industrial regions, cultural hubs like Cologne and Düsseldorf, and numerous universities and research institutions.
-
B.
Rhineland-Palatinate
Rhineland-Palatinate is a federal state in western Germany known for its wine-growing regions along the Rhine and Moselle rivers and its historic cities such as Mainz and Trier.
-
C.
South Westphalia
South Westphalia is a region in western Germany known for its mixed industrial and rural character, encompassing parts of North Rhine-Westphalia including the Arnsberg area.
-
D.
NRW
NRW is the three-letter National Rail station code used to identify Norwich railway station in the UK rail network.
-
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 (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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df565dc819099537fc06b694b40 |
completed | March 31, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd94c7db688190a755d0143c71c2b2 |
completed | April 1, 2026, 9:57 p.m. |
Created at: March 30, 2026, 5:43 p.m.