Triple
T26283048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Clair |
E661054
|
entity |
| Predicate | borderCountryAcrossRiver |
P118144
|
FINISHED |
| Object | United States of America |
—
|
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: United States of America | Statement: [St. Clair, borderCountryAcrossRiver, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderCountryAcrossRiver Context triple: [St. Clair, borderCountryAcrossRiver, United States of America]
-
A.
borderedByCountryAcrossRiver
chosen
Indicates that one country shares a border with another country, with the boundary specifically formed or separated by a river.
-
B.
bordersAcrossRiver
Indicates that two regions or entities share a boundary with each other that is separated or defined by a river.
-
C.
crossedByRiver
Indicates that a river passes across or through a specified area, feature, or route.
-
D.
nearbyCountryAcrossRiver
Indicates that one country is located close to another country with a river lying between them as a separating feature.
-
E.
locatedAcrossRiverFrom
Indicates that one entity is situated on the opposite side of a river relative to 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_69ee812bbd448190be4d7478b057990a |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 26, 2026, 10:02 p.m.