Triple
T11622636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appenzell |
E276175
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Appenzell (town) |
E276175
|
NE FINISHED |
How this triple was built (2 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: Appenzell (town) | Statement: [Appenzell, hasCapital, Appenzell (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Appenzell (town) Context triple: [Appenzell, hasCapital, Appenzell (town)]
-
A.
Appenzell
chosen
Appenzell is a historic region and former canton in northeastern Switzerland, known for its rural traditions, distinctive culture, and picturesque Alpine landscapes.
-
B.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
C.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
-
D.
Antdorf
Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
-
E.
Bonstetten
Bonstetten is a small municipality in the Swabian region of Bavaria in southern Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a122a3708190ab6513dad4c4fde7 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee8762586481909a4b563c827487e0 |
completed | April 26, 2026, 9:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.