Triple
T14237890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borås |
E352932
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Espelkamp
Espelkamp is a small town in North Rhine-Westphalia, Germany, known for its post-war planned layout and light industrial economy.
|
E1162741
|
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: Espelkamp | Statement: [Borås, hasTwinTown, Espelkamp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espelkamp Context triple: [Borås, hasTwinTown, Espelkamp]
-
A.
Nettersheim
Nettersheim is a municipality in the Eifel region of North Rhine-Westphalia, Germany, known for its natural landscapes and archaeological sites.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Rüdinghausen
Rüdinghausen is a district of the city of Witten in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
-
D.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
E.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan 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: Espelkamp Triple: [Borås, hasTwinTown, Espelkamp]
Generated description
Espelkamp is a small town in North Rhine-Westphalia, Germany, known for its post-war planned layout and light industrial economy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Espelkamp Target entity description: Espelkamp is a small town in North Rhine-Westphalia, Germany, known for its post-war planned layout and light industrial economy.
-
A.
Nettersheim
Nettersheim is a municipality in the Eifel region of North Rhine-Westphalia, Germany, known for its natural landscapes and archaeological sites.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Rüdinghausen
Rüdinghausen is a district of the city of Witten in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
-
D.
Breckerfeld
Breckerfeld is a small town in North Rhine-Westphalia, Germany, known for its rural character and location in the hilly, forested region of the Sauerland.
-
E.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62422e28819089e7115052a28c96 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d379bc881908b7954c633787165 |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff419dbffc8190bab9ae378e2f6858 |
completed | May 9, 2026, 2:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff41e95bf08190965a870acb72edb6 |
completed | May 9, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:08 a.m.