Triple
T1760277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlington Boulevard |
E38640
|
entity |
| Predicate | hasGradeSeparatedInterchanges |
P31430
|
FINISHED |
| Object | at some major junctions |
—
|
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: at some major junctions | Statement: [Arlington Boulevard, hasGradeSeparatedInterchanges, at some major junctions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGradeSeparatedInterchanges Context triple: [Arlington Boulevard, hasGradeSeparatedInterchanges, at some major junctions]
-
A.
isMajorInterchangeFor
Indicates that one location functions as a primary hub where multiple routes or lines connect or transfer between each other for another location.
-
B.
hasExpressLanes
Indicates that a roadway or transportation facility includes designated express lanes for faster or prioritized travel.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
E.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab173830a481908b67928f16f5d999 |
completed | March 6, 2026, 6:04 p.m. |
Created at: March 4, 2026, 7:31 p.m.