Triple
T14542521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine–New Brunswick border |
E341204
|
entity |
| Predicate | passesNearSettlement |
P3945
|
FINISHED |
| Object | Madawaska, Maine |
—
|
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: Madawaska, Maine | Statement: [Maine–New Brunswick border, passesNearSettlement, Madawaska, Maine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passesNearSettlement Context triple: [Maine–New Brunswick border, passesNearSettlement, Madawaska, Maine]
-
A.
passesNearCity
chosen
Indicates that the path, route, or trajectory of one entity goes close to, but not necessarily through, a specified city.
-
B.
passesCity
Indicates that a route, path, or journey goes through or traverses a particular city as part of its course.
-
C.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
D.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
E.
isLocatedOnOutskirtsOf
Indicates that one entity is situated on the outer edge or peripheral area of another entity, rather than in its central or inner part.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1be5a8081909bf727e28a5bba4a |
completed | April 14, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:22 a.m.