Triple
T21259132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warendorf district |
E523949
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Ems |
—
|
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: Ems | Statement: [Warendorf district, locatedOnRiver, Ems]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ems Context triple: [Warendorf district, locatedOnRiver, Ems]
-
A.
Ems
chosen
The Ems is a river in northwestern Germany that flows through several states before emptying into the North Sea.
-
B.
Ems
Ems is a historic spa town in present-day Germany, renowned for its mineral springs and 19th-century status as a fashionable European resort.
-
C.
Emsdetten
Emsdetten is a town in the district of Steinfurt in North Rhine-Westphalia, Germany, known for its textile industry heritage and location along the Ems River.
-
D.
Emst
Emst is a small village in the Dutch province of Gelderland, known as part of the municipality of Epe in the Veluwe region.
-
E.
Rhens
Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e53df88190bd6024793a0ada08 |
completed | April 21, 2026, 8:31 a.m. |
Created at: April 16, 2026, 3:59 p.m.