Triple

T32815057
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Lankwitz station E839262 entity
Predicate hasLocalPublicTransportConnection P15438 FINISHED
Object yes LITERAL 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: yes | Statement: [Berlin-Lankwitz station, hasLocalPublicTransportConnection, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLocalPublicTransportConnection
Context triple: [Berlin-Lankwitz station, hasLocalPublicTransportConnection, yes]
  • A. hasPublicTransportConnection
    Indicates that there is an available public transportation link or service connecting the related entities.
  • B. hasGoodPublicTransportConnections
    Indicates that an entity is well served by public transportation options, providing convenient and efficient connections to other locations.
  • C. hasPublicTransitNode
    Indicates that there exists a public transportation stop, station, or node associated with or located at the referenced entity.
  • D. hasPublicTransportStop chosen
    Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
  • E. hasPublicTransitRoute
    Indicates that there exists a public transportation route (such as a bus, train, or tram line) connecting or serving the related entities.
  • F. None of above.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fe349879848190bcd77e3cc3470458 completed May 8, 2026, 7:08 p.m.
PD Predicate disambiguation batch_69fe31e3cf908190b23ebc2f7fe58722 completed May 8, 2026, 6:56 p.m.
Created at: May 1, 2026, 1:15 a.m.