Triple
T5304771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CH-BS |
E120070
|
entity |
| Predicate | isUrbanCanton |
P63948
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [CH-BS, isUrbanCanton, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanCanton Context triple: [CH-BS, isUrbanCanton, true]
-
A.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
B.
isUrbanCommuneOf
Indicates that one entity is an urban commune that administratively belongs to or is part of another entity (typically a higher-level territorial unit).
-
C.
largestCantonByPopulation
Indicates that the subject is the canton with the highest population among a specified set or within a given region.
-
D.
isUrbanCentreFor
Indicates that one place functions as the primary urban hub or central city serving another area or population.
-
E.
canton
Indicates that an entity is administratively located within, belongs to, or is governed as part of a specific canton.
- F. None of above. chosen
Provenance (4 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_69bd44704be88190acdb2ac481b0ff55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd8e43c4c88190bb72b9bf56c99425 |
completed | March 20, 2026, 6:13 p.m. |
Created at: March 20, 2026, 1:53 p.m.