Triple

T2925541
Position Surface form Disambiguated ID Type / Status
Subject Ted Williams Tunnel E78833 entity
Predicate tollSystem P3913 FINISHED
Object E-ZPass E54620 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: E-ZPass | Statement: [Ted Williams Tunnel, tollSystem, E-ZPass]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: E-ZPass
Context triple: [Ted Williams Tunnel, tollSystem, E-ZPass]
  • A. E-ZPass chosen
    E-ZPass is an electronic toll collection system widely used on highways and bridges across the eastern United States, allowing drivers to pay tolls automatically without stopping.
  • B. FasTrak
    FasTrak is an electronic toll collection system used on bridges, roads, and express lanes throughout California.
  • C. TollTag
    TollTag is an electronic toll collection system used on North Texas toll roads, allowing drivers to pay tolls automatically without stopping.
  • D. Clipper card
    The Clipper card is a reloadable contactless smart card used to pay fares across multiple public transit systems in the San Francisco Bay Area.
  • E. SmarTrip
    SmarTrip is a rechargeable contactless smart card used to pay fares on the Washington, D.C. region’s public transit systems.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97c086888190ba51ce659a6c4f50 completed March 8, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0563a81788190b94fab34e41a76e7 completed March 10, 2026, 5:34 p.m.
Created at: March 8, 2026, 2:55 p.m.