Triple

T3494666
Position Surface form Disambiguated ID Type / Status
Subject 4th and Brannan station E73821 entity
Predicate fareSystem P395 FINISHED
Object Clipper E123351 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: Clipper | Statement: [4th and Brannan station, fareSystem, Clipper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clipper
Context triple: [4th and Brannan station, fareSystem, Clipper]
  • A. Clipper chosen
    Clipper is a reloadable contactless smart card system used for paying fares on public transit across the San Francisco Bay Area.
  • B. Corsair
    Corsair is a computer hardware and peripherals company best known for its gaming-focused products such as keyboards, mice, headsets, and PC components.
  • C. Scudder
    Scudder is a family surname that may refer to various individuals, including the fictional Mrs. Scudder and other real or literary figures bearing that name.
  • D. Blackrod
    Blackrod is a small town and civil parish in Greater Manchester, England, historically part of Lancashire and situated near Horwich and Bolton.
  • E. Orneta
    Orneta is a small historic town in northern Poland known for its medieval architecture and location within the picturesque Warmian-Masurian region.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbaebed881909d9cbc9c4c1f138f completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373c5e1248190a4c42805fb9363f0 completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:18 p.m.