Triple

T13537060
Position Surface form Disambiguated ID Type / Status
Subject U5 E323287 entity
Predicate operator P179 FINISHED
Object VGF E800184 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: VGF | Statement: [U5, operator, VGF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VGF
Context triple: [U5, operator, VGF]
  • A. VGF chosen
    VGF is the municipal public transport operator responsible for running Frankfurt am Main’s urban transit network, including its U-Bahn and tram services.
  • B. VGC
    VGC is a prominent upscale residential and commercial estate located in the Eti-Osa area of Lagos, Nigeria.
  • C. VGT
    VGT is the IATA airport code for North Las Vegas Airport, a general aviation facility serving the Las Vegas area in Nevada, USA.
  • D. VGN
    VGN (Verkehrsverbund Großraum Nürnberg) is the public transport association that coordinates and manages integrated ticketing and services across the greater Nuremberg metropolitan area in Germany.
  • E. VG
    VG is the two-letter ISO 3166 country code assigned to the British Virgin Islands.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafbe39948190808062d4eff91841 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f84935c8190b9e41f44140066e5 completed May 3, 2026, 5:01 p.m.
Created at: April 9, 2026, 9:45 p.m.