Triple

T10450767
Position Surface form Disambiguated ID Type / Status
Subject Berliner Bezirk Spandau E246414 entity
Predicate hasTransport P1298 FINISHED
Object S-Bahn-Linie S9 E608018 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-Linie S9 | Statement: [Berliner Bezirk Spandau, hasTransport, S-Bahn-Linie S9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn-Linie S9
Context triple: [Berliner Bezirk Spandau, hasTransport, S-Bahn-Linie S9]
  • A. Berlin S-Bahn line S9 chosen
    Berlin S-Bahn line S9 is a suburban rail service in Berlin that connects the city center with Berlin Brandenburg Airport and other eastern and western districts as part of the S-Bahn network.
  • B. S-Bahn Ringbahn
    The S-Bahn Ringbahn is Berlin’s circular urban rail line that loops around the inner city, connecting numerous districts and major transport hubs.
  • C. S-Bahn line S1
    S-Bahn line S1 is a commuter rail service in the Berlin S-Bahn network that connects central Berlin with its northern and southwestern suburbs.
  • D. S7 Line
    The S7 Line is a suburban rapid transit line of the Nanjing Metro serving outlying districts to the south of Nanjing, China.
  • E. S8 (Munich S-Bahn)
    S8 is a Munich S-Bahn commuter rail line that connects central Munich with Munich Airport and other eastern and western suburbs.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe0a6a548190a54212912f618e4e completed April 7, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89fb27f5081909e78bd8029e65948 completed April 10, 2026, 6:58 a.m.
Created at: April 6, 2026, 12:17 p.m.