Triple
T10078677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheydt |
E213840
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Rhineland |
E60266
|
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: Rhineland | Statement: [Rheydt, historicalRegion, Rhineland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rhineland Context triple: [Rheydt, historicalRegion, Rhineland]
-
A.
Rhineland
chosen
The Rhineland is a historically significant region in western Germany along the Rhine River, long contested as a strategic and economic heartland in European conflicts.
-
B.
Rijnland
Rijnland is a historical region in the western Netherlands, centered around the lower Rhine delta and known for its extensive water management and polder landscapes.
-
C.
Rhine-Weser region
The Rhine-Weser region is a historical area in western Germany associated with the early homeland and formation of the Frankish people.
-
D.
Westphalia
Westphalia is a historical region in northwestern Germany known for being the site of the 1648 treaties that ended the Thirty Years' War and reshaped the political order of Europe.
-
E.
Siegerland
Siegerland is a hilly, forested region in western Germany known for its historic iron ore mining and metalworking industry.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd030a0fc819084b523e8e63636fa |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30041f8a88190b24de139e4acf9bb |
completed | April 6, 2026, 12:37 a.m. |
Created at: March 30, 2026, 9 p.m.