Triple

T16972460
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Westkreuz station E411719 entity
Predicate servedByLine P1293 FINISHED
Object S9 E142490 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: S9 | Statement: [Berlin-Westkreuz station, servedByLine, S9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S9
Context triple: [Berlin-Westkreuz station, servedByLine, S9]
  • A. S9 chosen
    S9 is a line of the Berlin S-Bahn rapid transit network that connects Berlin Brandenburg Airport with central and western parts of the city.
  • B. S9
    S9 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting multiple cities across the area.
  • C. S10
    S10 is a line of the Zürich S-Bahn suburban rail network serving the Uetliberg mountain area.
  • D. S91
    S91 is a Staten Island local bus route in New York City that provides public transit service through neighborhoods including New Springville.
  • E. Moonton
    Moonton is a Chinese video game developer best known for creating the popular mobile multiplayer online battle arena game Mobile Legends: Bang Bang.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0ae47f08190a13e98d20aba7f16 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d471d4248190acf40b6c11926a65 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.