Triple

T6230919
Position Surface form Disambiguated ID Type / Status
Subject S7 E139349 entity
Predicate viaStation P64719 FINISHED
Object Lichtenberg E38727 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: Lichtenberg | Statement: [S7, viaStation, Lichtenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichtenberg
Context triple: [S7, viaStation, Lichtenberg]
  • A. Lichtenberg chosen
    Lichtenberg is a borough in eastern Berlin, Germany, known for its mix of residential areas, historical sites, and former Soviet administrative and military facilities.
  • B. Reichenbach
    Reichenbach is a German surname most notably associated with Hans Reichenbach, a prominent 20th-century philosopher of science and logical empiricist.
  • C. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • D. Lilienthal
    Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
  • E. Schöngarth
    Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
  • 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_69c008afd3148190b71e9eaa60420dd1 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062ec5be4819084d6df2e8dd2a542 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20de90ba08190be1e0c44b5b13f53 completed March 24, 2026, 4:07 a.m.
Created at: March 22, 2026, 4:22 p.m.