Triple
T19472857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planken |
E487167
|
entity |
| Predicate | sharesNationalGovernmentWith |
P48855
|
FINISHED |
| Object | Ruggell |
—
|
NE NERFINISHED |
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: Ruggell | Statement: [Planken, sharesNationalGovernmentWith, Ruggell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruggell Context triple: [Planken, sharesNationalGovernmentWith, Ruggell]
-
A.
Ruggell
chosen
Ruggell is a northern Liechtenstein municipality known for its flat Rhine valley landscape and agricultural character.
-
B.
Schaan
Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
-
C.
Balzers
Balzers is a municipality in southern Liechtenstein known for its scenic Alpine setting and historic Gutenberg Castle.
-
D.
Uster
Uster is a Swiss town and municipality in the canton of Zürich, known as a regional center near Lake Greifen with a mix of urban amenities and surrounding natural landscapes.
-
E.
Schafhausen
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633ea604c8190a2feacb709b7ca27 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:39 p.m.