Triple

T19478381
Position Surface form Disambiguated ID Type / Status
Subject K-TAG E487312 entity
Predicate tollAssessmentMethod P3913 FINISHED
Object electronic gantry readers 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: electronic gantry readers | Statement: [K-TAG, tollAssessmentMethod, electronic gantry readers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tollAssessmentMethod
Context triple: [K-TAG, tollAssessmentMethod, electronic gantry readers]
  • A. tollingType chosen
    Indicates the specific method or basis by which a toll, fee, or charge is applied or calculated in a given context.
  • B. typeOfTollSystem
    Indicates the specific kind or category of toll collection system used in a given context.
  • C. appliesTollTo
    Indicates that a fee or charge is imposed on a subject for using, accessing, or passing through something.
  • D. tollingAuthority
    Indicates the entity that has the authority to impose, collect, or manage a toll on a given route, facility, or service.
  • E. hasToll
    Indicates that the use, access, or passage associated with something requires payment of a toll or fee.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63437b9748190a8fc6bf6b3d90918 completed April 20, 2026, 2:12 p.m.
PD Predicate disambiguation batch_69e4fd7883308190b73912a71a35a835 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 1:39 p.m.