Triple

T6194323
Position Surface form Disambiguated ID Type / Status
Subject Dallas North Tollway E138471 entity
Predicate tollCollection P395 FINISHED
Object EZ TAG E256093 NE 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: EZ TAG | Statement: [Dallas North Tollway, tollCollection, EZ TAG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EZ TAG
Context triple: [Dallas North Tollway, tollCollection, EZ TAG]
  • A. EZ TAG chosen
    EZ TAG is an electronic toll collection system used on certain Texas toll roads that allows drivers to pay tolls automatically without stopping.
  • B. K-TAG
    K-TAG is an electronic toll collection system used on the Kansas Turnpike and compatible highways, allowing drivers to pay tolls automatically via a windshield-mounted transponder.
  • C. TollTag
    TollTag is an electronic toll collection system used on North Texas toll roads, allowing drivers to pay tolls automatically without stopping.
  • D. TxTag
    TxTag is an electronic toll collection system used on Texas toll roads that allows drivers to pay tolls automatically without stopping.
  • E. ATAG
    ATAG (Authoring Tool Accessibility Guidelines) is a W3C specification that defines how software used to create web content should support accessibility both in its user interface and in the content it produces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062443cec81909dc9bafea2f5e7d4 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f1c162081909cf34e827f1bd7d7 completed March 23, 2026, 4:49 p.m.
Created at: March 22, 2026, 4:19 p.m.