Triple
T3268266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancy |
E68579
|
entity |
| Predicate | hasCantonCode |
P28599
|
FINISHED |
| Object | GE |
—
|
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: GE | Statement: [Lancy, hasCantonCode, GE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCantonCode Context triple: [Lancy, hasCantonCode, GE]
-
A.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
B.
cantonCode
chosen
Indicates the specific administrative canton identifier associated with an entity or location.
-
C.
includesCanton
Indicates that a larger administrative or geographic entity contains or encompasses a specific canton within its boundaries.
-
D.
largestCantonByPopulation
Indicates that the subject is the canton with the highest population among a specified set or within a given region.
-
E.
featuresCanton
Indicates that an administrative region or entity includes or is associated with a specific canton as one of its subdivisions or components.
- F. None of above.
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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcf9c6c819092f9c618b778b46d |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada41d7eac8190ada4bf5f793d5c49 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.