Triple

T16858723
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Moabit E409853 entity
Predicate hasTransportConnection P845 FINISHED
Object S-Bahn line S7 E464113 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: S-Bahn line S7 | Statement: [Berlin-Moabit, hasTransportConnection, S-Bahn line S7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn line S7
Context triple: [Berlin-Moabit, hasTransportConnection, S-Bahn line S7]
  • A. S-Bahn line S75
    S-Bahn line S75 is a Berlin suburban rail service that connects the northeastern district of Neu-Hohenschönhausen with central parts of the city as part of the Berlin S-Bahn network.
  • B. S7 line chosen
    The S7 line is a Berlin S-Bahn railway service that runs east–west across the city, connecting key districts and suburbs as part of the German capital’s urban transit network.
  • C. S7 line
    The S7 line is a suburban railway service of the Zürich S-Bahn network that connects the city of Zürich with surrounding municipalities along Lake Zürich.
  • D. S7 line
    The S7 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt am Main region in Germany.
  • E. S-Bahn line S6
    S-Bahn line S6 is a regional suburban rail service in Germany’s Rhine-Ruhr network, connecting cities such as Essen and Düsseldorf and serving areas around Lake Baldeney (Baldeneysee).
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b37ef4748190b149d98fc0ab4205 completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb25300c8190a352037c21c244bd completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.