Triple
T6158457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amtrak Vermonter |
E137381
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Vermonter |
E163704
|
NE 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: Vermonter | Statement: [Amtrak Vermonter, name, Vermonter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vermonter Context triple: [Amtrak Vermonter, name, Vermonter]
-
A.
Vermonter
chosen
The Vermonter is an Amtrak intercity passenger train that runs between Washington, D.C., and St. Albans, Vermont, serving major cities along the Northeast Corridor and New England.
-
B.
Vermont
Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
-
C.
Vermont
Vermont is a small rural town located in Dane County, Wisconsin, known for its scenic landscapes and agricultural character.
-
D.
Warren, Vermont
Warren, Vermont is a small New England town in the Mad River Valley known for its scenic mountain setting, outdoor recreation, and proximity to Sugarbush Resort.
-
E.
Vermont-Slauson
Vermont-Slauson is a predominantly residential and commercial neighborhood in South Los Angeles known for its diverse community and urban character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008a54fc88190b6ce4416490ca79d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d32ef548190bc215d052d3497fe |
completed | March 22, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1419064a48190880005459c86322c |
completed | March 23, 2026, 1:35 p.m. |
Created at: March 22, 2026, 4:17 p.m.