Triple
T14938426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colmar-Berg |
E372457
|
entity |
| Predicate | hasNeighbouringCommune |
P33892
|
FINISHED |
| Object |
Vichten
Vichten is a small rural commune and village located in central Luxembourg.
|
E1128619
|
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: Vichten | Statement: [Colmar-Berg, hasNeighbouringCommune, Vichten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vichten Context triple: [Colmar-Berg, hasNeighbouringCommune, Vichten]
-
A.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
B.
Vezhof
Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
-
C.
Vohwinkel
Vohwinkel is a district in the German city of Wuppertal, historically an independent town before being incorporated during municipal reforms.
-
D.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
E.
Valtice
Valtice is a historic town in the South Moravian Region of the Czech Republic, renowned for its Baroque chateau, vineyards, and role as a key part of the Lednice–Valtice cultural landscape.
- 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: Vichten Triple: [Colmar-Berg, hasNeighbouringCommune, Vichten]
Generated description
Vichten is a small rural commune and village located in central Luxembourg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vichten Target entity description: Vichten is a small rural commune and village located in central Luxembourg.
-
A.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
-
B.
Vezhof
Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
-
C.
Vohwinkel
Vohwinkel is a district in the German city of Wuppertal, historically an independent town before being incorporated during municipal reforms.
-
D.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
E.
Valtice
Valtice is a historic town in the South Moravian Region of the Czech Republic, renowned for its Baroque chateau, vineyards, and role as a key part of the Lednice–Valtice cultural landscape.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64904d88190b6b4140da8e8199d |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e8e9c0c81909cfb1e02987527c0 |
completed | May 9, 2026, 12:23 a.m. |
| NEDg | Description generation | batch_69fe7f299cf081909a3e15ead54bd2fc |
completed | May 9, 2026, 12:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe7fb4aa5c8190bca9fc60a1ef6833 |
completed | May 9, 2026, 12:28 a.m. |
Created at: April 10, 2026, 2:38 a.m.