Triple
T1346486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 495 (Capital Beltway) |
E28581
|
entity |
| Predicate | beltwayType |
P26847
|
FINISHED |
| Object | full circumferential loop |
—
|
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: full circumferential loop | Statement: [Interstate 495 (Capital Beltway), beltwayType, full circumferential loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beltwayType Context triple: [Interstate 495 (Capital Beltway), beltwayType, full circumferential loop]
-
A.
beltwayAround
Indicates that one roadway or route functions as a beltway encircling or surrounding another specified area or location.
-
B.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
C.
outerBeltwayFor
Indicates that one roadway or route functions as an outer beltway encircling or bypassing the area served by another route or location.
-
D.
guidewayType
Indicates the specific kind or classification of guideway used in a transportation or movement system.
-
E.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
- F. None of above. chosen
Provenance (4 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23e84188190b0395c57dd45b62a |
completed | March 1, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69a4bef5857c81909ae984feb85a26ca |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf60545c8190901ccfb2cb7c4b41 |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:56 p.m.