Triple

T11268082
Position Surface form Disambiguated ID Type / Status
Subject San Diego Metropolitan Transit System E266739 entity
Predicate fareSystem P395 FINISHED
Object Pronto E381796 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: Pronto | Statement: [San Diego Metropolitan Transit System, fareSystem, Pronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pronto
Context triple: [San Diego Metropolitan Transit System, fareSystem, Pronto]
  • A. Pronto
    Pronto is a crime novel by Elmore Leonard that introduces the character U.S. Marshal Raylan Givens in a fast-paced story of mobsters, hitmen, and a bookie on the run.
  • B. PRONTO chosen
    PRONTO is a contactless, account-based fare payment system used for public transit services in San Diego County, California.
  • C. Rapido
    Rapido is an Indian app-based bike taxi and logistics platform that offers affordable two-wheeler rides and deliveries in urban areas.
  • D. On Call
    "On Call" is a collection of essays by poet and activist June Jordan that blends personal narrative with incisive commentary on race, gender, politics, and social justice.
  • E. Toinette
    Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e94f60d48190bc925c3cb88641a8 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ccd52c20819093e03bba2fd359b7 completed April 19, 2026, 12:38 p.m.
Created at: April 8, 2026, 9:31 p.m.