Triple
T15940472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Appenzell Ausserrhoden |
E386544
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Heiden |
E50277
|
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: Heiden | Statement: [canton of Appenzell Ausserrhoden, hasMunicipality, Heiden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heiden Context triple: [canton of Appenzell Ausserrhoden, hasMunicipality, Heiden]
-
A.
Heiden
Heiden is a municipality in the Borken district of North Rhine-Westphalia in western Germany, known for its rural character and local cultural traditions.
-
B.
Heiden
chosen
Heiden is a municipality in the Swiss canton of Appenzell Ausserrhoden, known as the place where Red Cross founder Henry Dunant spent his final years and died.
-
C.
Heiden
Heiden is the central hall of worship within Japan’s Itsukushima Shrine, used for Shinto religious ceremonies and offerings.
-
D.
Heidiland
Heidiland is a popular Swiss tourist region in Eastern Switzerland, known for its alpine landscapes and associations with Johanna Spyri’s "Heidi" stories.
-
E.
Stockheim
Stockheim is a village and district of the town of Brackenheim in the Heilbronn district of Baden-Württemberg, 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_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. |
Created at: April 10, 2026, 4:53 a.m.