Triple

T11970901
Position Surface form Disambiguated ID Type / Status
Subject Texas State Highway 130 E284915 entity
Predicate hasTollingSystem P73181 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: [Texas State Highway 130, hasTollingSystem, EZ TAG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EZ TAG
Context triple: [Texas State Highway 130, hasTollingSystem, 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037d32e88190b1509285dc907d29 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459691ff0819099282172933d2d81 completed May 1, 2026, 7:42 a.m.
Created at: April 8, 2026, 9:46 p.m.