Triple
T22405977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vetera |
E553880
|
entity |
| Predicate | nearModern |
P33888
|
FINISHED |
| Object | Xanten, Germany |
—
|
NE NERFINISHED |
How this triple was built (4 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: Xanten, Germany | Statement: [Vetera, nearModern, Xanten, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xanten, Germany Context triple: [Vetera, nearModern, Xanten, Germany]
-
A.
Lüdenscheid, Germany
Lüdenscheid is a town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its metal and plastics industries and its location in the Sauerland region.
-
B.
Hamm, Germany
Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
-
C.
Dulmen, Germany
Dülmen is a town in the Münster region of North Rhine-Westphalia in western Germany, known for its surrounding nature reserves and the famous herd of wild horses in the nearby Merfelder Bruch.
-
D.
Kempen, Germany
Kempen is a historic town in western Germany’s North Rhine-Westphalia region, known for its well-preserved medieval center and cultural ties to other European cities.
-
E.
Rheine, Germany
Rheine, Germany is a city in the state of North Rhine-Westphalia known as an industrial and transportation hub in northwestern Germany.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xanten, Germany Target entity description: Xanten, Germany is a historic town on the Lower Rhine renowned for its well-preserved Roman archaeological sites and medieval architecture.
-
A.
Lüdenscheid, Germany
Lüdenscheid is a town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its metal and plastics industries and its location in the Sauerland region.
-
B.
Hamm, Germany
Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
-
C.
Dulmen, Germany
Dülmen is a town in the Münster region of North Rhine-Westphalia in western Germany, known for its surrounding nature reserves and the famous herd of wild horses in the nearby Merfelder Bruch.
-
D.
Kempen, Germany
Kempen is a historic town in western Germany’s North Rhine-Westphalia region, known for its well-preserved medieval center and cultural ties to other European cities.
-
E.
Rheine, Germany
Rheine, Germany is a city in the state of North Rhine-Westphalia known as an industrial and transportation hub in northwestern Germany.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearModern Context triple: [Vetera, nearModern, Xanten, Germany]
-
A.
nearModernSite
chosen
Indicates that one entity is located in close physical proximity to a site or location from the modern era.
-
B.
nearModernAvenue
Indicates that one entity is located close to or in the vicinity of a modern avenue.
-
C.
formedModern
Indicates that an entity created, established, or organized another entity in the modern era or in its current modern form.
-
D.
modernInfluence
Indicates that one entity has a shaping or impactful effect on another within a contemporary or current context.
-
E.
modernUse
Indicates how something is currently used or applied in modern times.
- F. None of above.
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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b835e88190a388e19577df771e |
completed | April 29, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:46 p.m.