Triple
T5147165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon, New Hampshire micropolitan area |
E116098
|
entity |
| Predicate | borderingStateRegion |
P10768
|
FINISHED |
| Object | eastern Vermont |
—
|
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: eastern Vermont | Statement: [Lebanon, New Hampshire micropolitan area, borderingStateRegion, eastern Vermont]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingStateRegion Context triple: [Lebanon, New Hampshire micropolitan area, borderingStateRegion, eastern Vermont]
-
A.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
-
B.
borderingStateOrTerritory
Indicates that one state or territory shares a common boundary with another state or territory.
-
C.
borderRegionOf
chosen
Indicates that one region lies along, touches, or forms part of the boundary of another region.
-
D.
provinceBordering
Indicates that two provinces share a common boundary or border with each other.
-
E.
borderRegionsInclude
Indicates that the specified border area encompasses or contains the referenced regions within its boundaries.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.