Triple

T2843231
Position Surface form Disambiguated ID Type / Status
Subject Massachusetts Route 3 E62517 entity
Predicate laneUsage P29561 FINISHED
Object automobile traffic 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: automobile traffic | Statement: [Massachusetts Route 3, laneUsage, automobile traffic]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: laneUsage
Context triple: [Massachusetts Route 3, laneUsage, automobile traffic]
  • A. roadUse chosen
    Indicates that an entity utilizes or travels on a particular road or roadway for movement or transport.
  • B. laneCount
    Indicates the number of parallel lanes associated with a given road or roadway segment.
  • C. hasWheelchairLanes
    Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
  • D. someRightOfWayUsedBy
    Indicates that a particular right of way is utilized or traversed by a specified user, route, or transport entity.
  • E. hasDedicatedLanes
    Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf1a07508190be35fe85733ddeed completed March 7, 2026, 8:17 a.m.
PD Predicate disambiguation batch_69abdd0e86808190bcefffafbd3cd441 completed March 7, 2026, 8:08 a.m.
Created at: March 6, 2026, 10:01 p.m.