Triple
T320484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 95 near Newport, Maine |
E6402
|
entity |
| Predicate | hasRestAreaNear |
P5648
|
FINISHED |
| Object | public rest areas and service facilities in the Newport vicinity |
—
|
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: public rest areas and service facilities in the Newport vicinity | Statement: [Interstate 95 near Newport, Maine, hasRestAreaNear, public rest areas and service facilities in the Newport vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestAreaNear Context triple: [Interstate 95 near Newport, Maine, hasRestAreaNear, public rest areas and service facilities in the Newport vicinity]
-
A.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
B.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
C.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
D.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
E.
hasNearbyTown
Indicates that one location has a town situated close to it in geographic proximity.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.