Triple
T8439302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhine-Ruhr metropolitan region |
E199309
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Neuss |
E147996
|
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: Neuss | Statement: [Rhine-Ruhr metropolitan region, containsCity, Neuss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neuss Context triple: [Rhine-Ruhr metropolitan region, containsCity, Neuss]
-
A.
Neuss
chosen
Neuss is a city in western Germany, near Düsseldorf, known as an administrative and commercial center with historical roots dating back to Roman times.
-
B.
Neunkirchen
Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
-
C.
Bitburg
Bitburg is a town in western Germany’s Eifel region, best known internationally for its Bitburger brewery and its nearby World War II military cemetery.
-
D.
Eschweiler
Eschweiler is a town in western Germany near Aachen, known for its industrial history and location in the state of North Rhine-Westphalia.
-
E.
Heinsberg
Heinsberg is a town in western Germany’s North Rhine-Westphalia near the Dutch border, known as the administrative center of the Heinsberg district.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe13708988190a534e38d8254c9bd |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfab16ebd08190a4851e70a41e9908 |
completed | April 3, 2026, 11:57 a.m. |
Created at: March 30, 2026, 6:08 p.m.