Triple

T12309792
Position Surface form Disambiguated ID Type / Status
Subject San Diego Freeway E293444 entity
Predicate hasCarpoolLanes P104384 FINISHED
Object yes 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: yes | Statement: [San Diego Freeway, hasCarpoolLanes, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCarpoolLanes
Context triple: [San Diego Freeway, hasCarpoolLanes, yes]
  • A. hasDedicatedLanes
    Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
  • B. hasLanes
    Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
  • C. hasExpressLanes
    Indicates that a roadway or transportation facility includes designated express lanes for faster or prioritized travel.
  • D. hasWheelchairLanes
    Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
  • E. hasTrackLanes
    Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f621570819091ee1db2609233ea completed April 10, 2026, 6:20 p.m.
PD Predicate disambiguation batch_69d93ec02c008190a56aae60a3d9eff6 completed April 10, 2026, 6:17 p.m.
PDg Predicate description generation batch_69d93f607a88819089e89fd263ae9937 completed April 10, 2026, 6:20 p.m.
Created at: April 8, 2026, 9:53 p.m.