Triple
T15940471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Appenzell Ausserrhoden |
E386544
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Teufen
Teufen is a Swiss municipality known for its picturesque setting in the hilly landscape of northeastern Switzerland and its traditional Appenzell architecture and culture.
|
E1185514
|
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: Teufen | Statement: [canton of Appenzell Ausserrhoden, hasMunicipality, Teufen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teufen Context triple: [canton of Appenzell Ausserrhoden, hasMunicipality, Teufen]
-
A.
Würges
Würges is a district of the spa town Bad Camberg in the Limburg-Weilburg region of Hesse, Germany.
-
B.
Nerenstetten
Nerenstetten is a small rural municipality in the Alb-Donau district of Baden-Württemberg in southern Germany.
-
C.
Grimeton
Grimeton is a locality in Sweden best known for hosting the historic VLF radio station SAQ, a UNESCO World Heritage Site.
-
D.
Falkenstein
Falkenstein is a district of the spa town Königstein im Taunus in Hesse, Germany, known for its scenic location in the Taunus mountains and historic castle ruins.
-
E.
Nachtwey
Nachtwey is the surname of James Nachtwey, a renowned American photojournalist celebrated for his powerful war and conflict photography.
- 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: Teufen Triple: [canton of Appenzell Ausserrhoden, hasMunicipality, Teufen]
Generated description
Teufen is a Swiss municipality known for its picturesque setting in the hilly landscape of northeastern Switzerland and its traditional Appenzell architecture and culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teufen Target entity description: Teufen is a Swiss municipality known for its picturesque setting in the hilly landscape of northeastern Switzerland and its traditional Appenzell architecture and culture.
-
A.
Würges
Würges is a district of the spa town Bad Camberg in the Limburg-Weilburg region of Hesse, Germany.
-
B.
Nerenstetten
Nerenstetten is a small rural municipality in the Alb-Donau district of Baden-Württemberg in southern Germany.
-
C.
Grimeton
Grimeton is a locality in Sweden best known for hosting the historic VLF radio station SAQ, a UNESCO World Heritage Site.
-
D.
Falkenstein
Falkenstein is a district of the spa town Königstein im Taunus in Hesse, Germany, known for its scenic location in the Taunus mountains and historic castle ruins.
-
E.
Nachtwey
Nachtwey is the surname of James Nachtwey, a renowned American photojournalist celebrated for his powerful war and conflict photography.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156cd3a188190a1a7dcbfdd38284c |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5ba070c8190b6af6cb21bddd7f1 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb77a69188190a7b4910a0ce2534c |
completed | May 9, 2026, 10:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffbbcd0a948190972ddf2202faa85b |
completed | May 9, 2026, 10:57 p.m. |
Created at: April 10, 2026, 4:53 a.m.