Triple
T6662526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A7 motorway (Switzerland) |
E151511
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object |
Matzingen
Matzingen is a municipality in the canton of Thurgau in northeastern Switzerland.
|
E647924
|
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: Matzingen | Statement: [A7 motorway (Switzerland), passesNear, Matzingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matzingen Context triple: [A7 motorway (Switzerland), passesNear, Matzingen]
-
A.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
B.
Meißenheim
Meißenheim is a small municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine River.
-
C.
Giengen an der Brenz
Giengen an der Brenz is a small town in the state of Baden-Württemberg in southern Germany, known as the birthplace of the Steiff teddy bear.
-
D.
Münklingen
Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
E.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
- 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: Matzingen Triple: [A7 motorway (Switzerland), passesNear, Matzingen]
Generated description
Matzingen is a municipality in the canton of Thurgau in northeastern Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matzingen Target entity description: Matzingen is a municipality in the canton of Thurgau in northeastern Switzerland.
-
A.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
B.
Meißenheim
Meißenheim is a small municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenau district near the Rhine River.
-
C.
Giengen an der Brenz
Giengen an der Brenz is a small town in the state of Baden-Württemberg in southern Germany, known as the birthplace of the Steiff teddy bear.
-
D.
Münklingen
Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
E.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
- 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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b097e0e481909251443f9ce0b85a |
completed | March 27, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf66c0308190a09736eafe61c966 |
completed | March 28, 2026, 11:45 a.m. |
| NEDg | Description generation | batch_69c7bff630d88190a8c8d4194a1fe763 |
completed | March 28, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7c05fd088819083df4c7167216ca2 |
completed | March 28, 2026, 11:49 a.m. |
Created at: March 27, 2026, 2:02 p.m.