Triple
T9558348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Achim |
E230602
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object |
Langwedel
Langwedel is a municipality in Lower Saxony, Germany, located in the district of Verden near the city of Bremen.
|
E806483
|
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: Langwedel | Statement: [Achim, hasNeighboringMunicipality, Langwedel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langwedel Context triple: [Achim, hasNeighboringMunicipality, Langwedel]
-
A.
Salzwedel
Salzwedel is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and as the birthplace of Jenny von Westphalen, the wife of Karl Marx.
-
B.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
C.
Fürstenwalde
Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
-
D.
Niederschöneweide
Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
-
E.
Sprockhövel
Sprockhövel is a small town in North Rhine-Westphalia, Germany, known for its historical coal mining heritage and location in the hilly Ruhr region.
- 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: Langwedel Triple: [Achim, hasNeighboringMunicipality, Langwedel]
Generated description
Langwedel is a municipality in Lower Saxony, Germany, located in the district of Verden near the city of Bremen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langwedel Target entity description: Langwedel is a municipality in Lower Saxony, Germany, located in the district of Verden near the city of Bremen.
-
A.
Salzwedel
Salzwedel is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and as the birthplace of Jenny von Westphalen, the wife of Karl Marx.
-
B.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
C.
Fürstenwalde
Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
-
D.
Niederschöneweide
Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
-
E.
Sprockhövel
Sprockhövel is a small town in North Rhine-Westphalia, Germany, known for its historical coal mining heritage and location in the hilly Ruhr region.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99487b4c819086e02e29e37b593f |
completed | April 1, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d15296303c8190adda4b24036d9390 |
completed | April 4, 2026, 6:04 p.m. |
| NEDg | Description generation | batch_69d1539bad8481909f9bd060aa3b651c |
completed | April 4, 2026, 6:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d154567f408190a848eea4ca905fb6 |
completed | April 4, 2026, 6:11 p.m. |
Created at: March 30, 2026, 8:03 p.m.