Triple
T11878471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Rhine region |
E282590
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Moers |
E495845
|
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: Moers | Statement: [Lower Rhine region, contains, Moers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moers Context triple: [Lower Rhine region, contains, Moers]
-
A.
Moers
chosen
Moers is a city in western Germany’s North Rhine-Westphalia, known as a former coal-mining center on the western edge of the Ruhr industrial region.
-
B.
Roermond
Roermond is a historic city in the southeastern Netherlands known for its medieval architecture, prominent churches, and large designer outlet shopping center.
-
C.
Münster
Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
-
D.
Xanten
Xanten is a historic town in western Germany known for its well-preserved Roman archaeological park and medieval architecture.
-
E.
Heerlen
Heerlen is a city in the southeastern Netherlands known for its mining history and modernist architecture, located in the province of Limburg.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8be1b6a5c81909a18c54205dda09c |
completed | April 10, 2026, 9:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281d8c65081908ebaf4bff5670c47 |
completed | April 29, 2026, 10:10 p.m. |
Created at: April 8, 2026, 9:44 p.m.