Triple
T11085714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendland region |
E262114
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lüchow
Lüchow is a small historic town in Lower Saxony, Germany, known as an administrative and cultural center of the rural Wendland area.
|
E905283
|
NE FINISHED |
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: Lüchow | Statement: [Wendland region, contains, Lüchow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lüchow Context triple: [Wendland region, contains, Lüchow]
-
A.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
-
B.
Ueckermünde
Ueckermünde is a small historic port town in northeastern Germany on the Szczecin Lagoon, known for its maritime heritage and access to the Baltic Sea.
-
C.
Gadebusch
Gadebusch is a small historic town in northern Germany known for its medieval architecture and rural surroundings.
-
D.
Prenzlau
Prenzlau is a historic town in northeastern Germany’s Brandenburg region, known for its medieval architecture and role as a regional administrative center.
-
E.
Lübbenau
Lübbenau is a small town in eastern Germany known as a popular gateway to the Spreewald biosphere reserve, famous for its canals and traditional punt boat tours.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lüchow Triple: [Wendland region, contains, Lüchow]
Generated description
Lüchow is a small historic town in Lower Saxony, Germany, known as an administrative and cultural center of the rural Wendland area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lüchow Target entity description: Lüchow is a small historic town in Lower Saxony, Germany, known as an administrative and cultural center of the rural Wendland area.
-
A.
Teterow
Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
-
B.
Ueckermünde
Ueckermünde is a small historic port town in northeastern Germany on the Szczecin Lagoon, known for its maritime heritage and access to the Baltic Sea.
-
C.
Gadebusch
Gadebusch is a small historic town in northern Germany known for its medieval architecture and rural surroundings.
-
D.
Prenzlau
Prenzlau is a historic town in northeastern Germany’s Brandenburg region, known for its medieval architecture and role as a regional administrative center.
-
E.
Lübbenau
Lübbenau is a small town in eastern Germany known as a popular gateway to the Spreewald biosphere reserve, famous for its canals and traditional punt boat tours.
- F. None of above. chosen
Provenance (5 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799c2c7d4819087ac793153340178 |
completed | April 9, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d66ded88190877a20a10f012d6b |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e42e1daa3c8190b598adcf9bac00f3 |
completed | April 19, 2026, 1:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e42f415b1081909f9eedcb3640cdc3 |
completed | April 19, 2026, 1:26 a.m. |
Created at: April 8, 2026, 9:27 p.m.