Triple
T7913017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic City Expressway |
E183744
|
entity |
| Predicate | hasRestFacility |
P29828
|
FINISHED |
| Object | service areas and parking areas along route |
—
|
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: service areas and parking areas along route | Statement: [Atlantic City Expressway, hasRestFacility, service areas and parking areas along route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestFacility Context triple: [Atlantic City Expressway, hasRestFacility, service areas and parking areas along route]
-
A.
hasRestAreas
chosen
Indicates that a route, location, or facility includes one or more designated rest areas available for use.
-
B.
hasMaintenanceFacilities
Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
-
C.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
D.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
servesFacility
Indicates that one entity provides services or support to a particular facility as its client, target, or area of operation.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a7383cc819084eab19799209d2e |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:04 p.m.