Triple
T12055364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Toggenburg |
E287026
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
St. Peterzell
St. Peterzell is a small village and former municipality in the Toggenburg region of the Swiss canton of St. Gallen.
|
E962002
|
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: St. Peterzell | Statement: [district of Toggenburg, contains, St. Peterzell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Peterzell Context triple: [district of Toggenburg, contains, St. Peterzell]
-
A.
Petershausen
Petershausen is a Bavarian municipality in southern Germany, located north of Munich and known for its rural character and good rail connections to the city.
-
B.
Pennenfeld
Pennenfeld is a residential subdistrict of the Bonn borough of Bad Godesberg in Germany.
-
C.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
-
D.
Osterburg
Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
-
E.
Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
- 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: St. Peterzell Triple: [district of Toggenburg, contains, St. Peterzell]
Generated description
St. Peterzell is a small village and former municipality in the Toggenburg region of the Swiss canton of St. Gallen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: St. Peterzell Target entity description: St. Peterzell is a small village and former municipality in the Toggenburg region of the Swiss canton of St. Gallen.
-
A.
Petershausen
Petershausen is a Bavarian municipality in southern Germany, located north of Munich and known for its rural character and good rail connections to the city.
-
B.
Pennenfeld
Pennenfeld is a residential subdistrict of the Bonn borough of Bad Godesberg in Germany.
-
C.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
-
D.
Osterburg
Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
-
E.
Wustermark
Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90425258c8190ba7b3b837c439253 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49dea043c8190a74ffb448bbae5d0 |
completed | May 1, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69f53d95d4fc8190b5f4e460646bec2a |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564d2b4348190abf2d09ae00aea37 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.