Triple

T8314745
Position Surface form Disambiguated ID Type / Status
Subject FDP E194677 entity
Predicate chairperson P377 FINISHED
Object Christian Lindner E279843 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: Christian Lindner | Statement: [FDP, chairperson, Christian Lindner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christian Lindner
Context triple: [FDP, chairperson, Christian Lindner]
  • A. Christian Lindner chosen
    Christian Lindner is a German politician who serves as the federal minister of finance and is a leading figure in Germany’s liberal political camp.
  • B. Christian Scholz
    Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
  • C. Sigmar Gabriel
    Sigmar Gabriel is a German Social Democratic politician who has served in prominent national roles including Vice Chancellor and Federal Minister for Foreign Affairs.
  • D. Thomas Kretschmann
    Thomas Kretschmann is a German actor known for his frequent roles in war and historical films, including notable performances in "The Pianist," "Downfall," and "King Kong."
  • E. Wolfgang Vogel
    Wolfgang Vogel was a prominent East German lawyer best known for brokering high-profile prisoner exchanges and political deals between East and West Germany during the Cold War.
  • 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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f52c5cc8190b5a95ee0aa4ddda5 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc6eca6408190abc34286cb7e8085 completed April 2, 2026, 1:31 a.m.
Created at: March 30, 2026, 5:55 p.m.