Triple

T10692943
Position Surface form Disambiguated ID Type / Status
Subject Tram 17 (Geneva) E252055 entity
Predicate fareSystem P395 FINISHED
Object unireso E127786 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: unireso | Statement: [Tram 17 (Geneva), fareSystem, unireso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: unireso
Context triple: [Tram 17 (Geneva), fareSystem, unireso]
  • A. unireso chosen
    unireso is the integrated public transport fare network for the Geneva region, coordinating tickets and tariffs across multiple operators and modes of transport.
  • B. UniGe
    UniGe is the commonly used abbreviation for the University of Genoa, a major public research university located in Genoa, Italy.
  • C. UniBE
    UniBE is the commonly used abbreviation for the University of Bern, a major public research university located in Bern, Switzerland.
  • D. Hokkaido University
    Hokkaido University is a major national research university in Sapporo, Japan, known for its broad academic offerings, strong science and agriculture programs, and spacious, park-like campus.
  • E. Osaka University
    Osaka University is a leading Japanese national research university known for its strong programs in science, engineering, and medicine and its major contributions to academic and industrial innovation.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd37cf408190a1912b3e0aa096a5 completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d988ad741c8190b9ae962e0c5bc272 completed April 10, 2026, 11:33 p.m.
Created at: April 8, 2026, 9:11 p.m.