Triple

T7413764
Position Surface form Disambiguated ID Type / Status
Subject Purple Line Express E171075 entity
Predicate fareIntegration P8545 FINISHED
Object Ventra E1909 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: Ventra | Statement: [Purple Line Express, fareIntegration, Ventra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ventra
Context triple: [Purple Line Express, fareIntegration, Ventra]
  • A. Ventra chosen
    Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
  • B. Evvy
    Evvy is a given name typically used as a short or affectionate form of longer names such as Evan or Evelyn.
  • C. Hertz
    Hertz is a German surname most famously associated with physicist Heinrich Hertz, after whom the unit of frequency is named.
  • D. Hertz
    Hertz is one of the concert halls within the TivoliVredenburg music complex in Utrecht, known for hosting a variety of live performances and cultural events.
  • E. Terminal 4S
    Terminal 4S is the satellite terminal of Madrid’s Adolfo Suárez Madrid–Barajas Airport, primarily serving international and long-haul flights with modern, high-capacity facilities.
  • 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_69c68a618bdc81908d8018edadecd1a4 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2c336308190932c14cec5eec25f completed March 27, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ee1b48c81909912ff0d7bf2837e completed March 28, 2026, 6:33 p.m.
Created at: March 27, 2026, 3:11 p.m.