Triple
T17946326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Salamanca, New York |
E448710
|
entity |
| Predicate | hasBorderRelationship |
P37800
|
FINISHED |
| Object | borders City of Salamanca, New York |
—
|
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: borders City of Salamanca, New York | Statement: [Town of Salamanca, New York, hasBorderRelationship, borders City of Salamanca, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderRelationship Context triple: [Town of Salamanca, New York, hasBorderRelationship, borders City of Salamanca, New York]
-
A.
hasBorderRelation
chosen
Indicates that one entity shares a boundary or border with another entity.
-
B.
hasBorderConnection
Indicates that two regions or entities share a common boundary or are directly connected along a border.
-
C.
hasBorderThrough
Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
-
D.
relatedBorder
Indicates that two geographic or political entities share a common boundary or border with each other.
-
E.
hasNeighborRelationshipWith
Indicates that one entity is located adjacent to or directly next to another entity, sharing a neighbor relationship.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad99df408190a8a4e3d21c03fe71 |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.