Triple

T12635666
Position Surface form Disambiguated ID Type / Status
Subject Bad Lausick station E301756 entity
Predicate serves P98 FINISHED
Object Bad Lausick E185206 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: Bad Lausick | Statement: [Bad Lausick station, serves, Bad Lausick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Lausick
Context triple: [Bad Lausick station, serves, Bad Lausick]
  • A. Bad Lausick chosen
    Bad Lausick is a small spa town in the Free State of Saxony in eastern Germany, known for its therapeutic mineral springs and health resorts.
  • B. Bad Laer
    Bad Laer is a small spa town in Lower Saxony, Germany, known for its therapeutic mineral springs and health tourism.
  • C. Bad Tennstedt
    Bad Tennstedt is a small spa town in Thuringia, Germany, known for its mineral springs and location in the Unstrut river landscape.
  • D. Bad Brambach
    Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
  • E. Bad Eilsen
    Bad Eilsen is a spa town in Lower Saxony, Germany, historically notable for serving as the post–World War II headquarters of the Royal Air Force’s British Air Forces of Occupation.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96147f49c8190b701e1e27e207a95 completed April 10, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6719886708190823f6f7e94e4d199 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:16 p.m.