Triple
T36253928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Lambton |
E891875
|
entity |
| Predicate | hasNearbyCountryAcrossBorder |
P126842
|
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: [Port Lambton, hasNearbyCountryAcrossBorder, United States of America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCountryAcrossBorder Context triple: [Port Lambton, hasNearbyCountryAcrossBorder, United States of America]
-
A.
hasCountryBorderWith
Indicates that two countries share a common land or maritime boundary.
-
B.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
C.
borderingCountryOnOtherSide
Indicates that one country lies on the opposite side of a shared border relative to another country.
-
D.
borderingCountryOfItsCountry
Indicates that one country shares a land or maritime border with another country.
-
E.
connectsToCountryBorder
chosen
Indicates that one entity is directly adjacent to and touches the border of a specified country.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a004d0b46148190bcec4ea67acfe170 |
completed | May 10, 2026, 9:16 a.m. |
| PD | Predicate disambiguation | batch_6a004c92283081909f229c1720af155a |
completed | May 10, 2026, 9:14 a.m. |
Created at: May 3, 2026, 4:09 p.m.