Triple
T11283365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lully (Geneva) |
E267119
|
entity |
| Predicate | isInBorderCanton |
P98297
|
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: [Lully (Geneva), isInBorderCanton, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInBorderCanton Context triple: [Lully (Geneva), isInBorderCanton, true]
-
A.
hasNeighbouringCanton
Indicates that one canton is geographically adjacent to and shares a common border with another canton.
-
B.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
C.
isBorderMunicipality
Indicates that a municipality is located on or directly adjacent to the border of a larger administrative region, country, or jurisdiction.
-
D.
includesCanton
Indicates that a larger administrative or geographic entity contains or encompasses a specific canton within its boundaries.
-
E.
borderTownOnSwissSide
Indicates that a town is located on the Swiss side of an international border.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e96e15708190b3a1cccfbbe65882 |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
| PDg | Predicate description generation | batch_69d796d049e88190a9fd7508f477f541 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:31 p.m.