Triple
T16736198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangor and Aroostook Railroad |
E406723
|
entity |
| Predicate | servedRuralAreas |
P80865
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bangor and Aroostook Railroad, servedRuralAreas, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedRuralAreas Context triple: [Bangor and Aroostook Railroad, servedRuralAreas, yes]
-
A.
servesRuralArea
chosen
Indicates that an entity provides services or support specifically to people or communities located in rural areas.
-
B.
ruralCoverage
Indicates the extent to which a service, infrastructure, or resource is available or provided in rural areas.
-
C.
hasRuralServiceTown
Indicates that a rural area or region is associated with, and typically receives services from, a specific town that functions as its service center.
-
D.
governsRuralArea
Indicates that one entity has governing authority or administrative control over a rural area associated with another entity.
-
E.
hasAdjacentMunicipalitiesServed
Indicates that a municipality has neighboring municipalities that are also served by the same service, system, or administrative arrangement.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3a86848190a03f243dd1bdb899 |
completed | April 18, 2026, 2:59 p.m. |
| PD | Predicate disambiguation | batch_69e319c807788190901250ab6e0ca55f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.