Triple
T1177944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey Route 27 |
E25070
|
entity |
| Predicate | hasRoadConfiguration |
P26277
|
FINISHED |
| Object | urban arterial segments |
—
|
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: urban arterial segments | Statement: [New Jersey Route 27, hasRoadConfiguration, urban arterial segments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadConfiguration Context triple: [New Jersey Route 27, hasRoadConfiguration, urban arterial segments]
-
A.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
-
B.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
C.
roadServed
Indicates that a road is provided with necessary services or infrastructure support by a responsible entity.
-
D.
hasTrafficIsland
Indicates the presence of a traffic island separating or organizing lanes or directions of vehicular movement within a roadway.
-
E.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd52177081908c5cec8e731b836e |
completed | March 1, 2026, 10:27 p.m. |
Created at: March 1, 2026, 7:45 p.m.