Triple
T32949425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calais, Maine |
E842900
|
entity |
| Predicate | hasNearbyCountrySubdivision |
P68114
|
FINISHED |
| Object | New Brunswick |
—
|
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: New Brunswick | Statement: [Calais, Maine, hasNearbyCountrySubdivision, New Brunswick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCountrySubdivision Context triple: [Calais, Maine, hasNearbyCountrySubdivision, New Brunswick]
-
A.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
-
B.
nearbyCountryProvince
Indicates that a province is geographically close to, or shares a border with, a specified country.
-
C.
geographicallyAdjacentTo
chosen
Indicates that two geographic entities share a common boundary or are directly next to each other in space.
-
D.
associatedCountrySubdivision
Indicates a relationship where an entity is linked to a specific administrative subdivision (such as a state, province, or region) within a country.
-
E.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
- 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_69f3494a31f481909057136e49b4fe60 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff64b957bc81908afbc5914234a8ea |
completed | May 9, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69ff6446593c81909173e296eea2590c |
completed | May 9, 2026, 4:43 p.m. |
Created at: May 1, 2026, 1:21 a.m.