Triple

T3381279
Position Surface form Disambiguated ID Type / Status
Subject U6 E71188 entity
Predicate terminusSouth P1866 FINISHED
Object Alt-Mariendorf E79213 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: Alt-Mariendorf | Statement: [U6, terminusSouth, Alt-Mariendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alt-Mariendorf
Context triple: [U6, terminusSouth, Alt-Mariendorf]
  • A. Alt-Mariendorf chosen
    Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
  • B. Friedrichsdorf
    Friedrichsdorf is a town in the German state of Hesse, located north of Frankfurt and known historically for its Huguenot heritage and proximity to the Taunus mountains.
  • C. Lichterfelde
    Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent character.
  • D. Langendorf
    Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
  • E. Lippendorf
    Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5e9af608190bfb228ef99a87bb7 completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3344f9b448190aab1038ead60fa48 completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:14 p.m.