Triple
T36159738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Présilly, Haute-Savoie |
E1045841
|
entity |
| Predicate | locatedInOrNextToBorder |
P46305
|
FINISHED |
| Object | Swiss border |
—
|
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: Swiss border | Statement: [Présilly, Haute-Savoie, locatedInOrNextToBorder, Swiss border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInOrNextToBorder Context triple: [Présilly, Haute-Savoie, locatedInOrNextToBorder, Swiss border]
-
A.
locatedNearStateBorderWith
Indicates that one entity is situated geographically close to the border of a specified state.
-
B.
hasNearbySettlementAcrossBorder
Indicates that one settlement is located close to another settlement that lies just across an intervening political or administrative border.
-
C.
nearInternationalBoundary
chosen
Indicates that one entity is located close to an international boundary separating two or more countries.
-
D.
connectsToCountryBorder
Indicates that one entity is directly adjacent to and touches the border of a specified country.
-
E.
borderedBy
Indicates that one entity shares a common boundary or edge with another entity.
- 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_69f76e38903c8190a52887620f90aabe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:08 p.m.