Triple

T17182290
Position Surface form Disambiguated ID Type / Status
Subject Schmitz E417012 entity
Predicate conflictWith P4897 FINISHED
Object Biedermann E1254385 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: Biedermann | Statement: [Schmitz, conflictWith, Biedermann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biedermann
Context triple: [Schmitz, conflictWith, Biedermann]
  • A. Biedermann chosen
    Biedermann is the central, complacent bourgeois protagonist in Max Frisch’s play "Biedermann und die Brandstifter," symbolizing willful ignorance in the face of rising danger.
  • B. Mr. Krupp
    Mr. Krupp is the grumpy elementary school principal who unknowingly transforms into the goofy superhero Captain Underpants in Dav Pilkey’s children’s book series.
  • C. Baerbel
    Baerbel is a feminine given name of German origin, commonly used as an alternative spelling of Bärbel.
  • D. Tebbe
    Tebbe is a German surname that serves as the etymological root for the name Tibbets.
  • E. Mr. Keuner
    Mr. Keuner is a philosophical everyman figure created by Bertolt Brecht, used in a series of parable-like stories to explore ethical, political, and existential questions.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42d934ec08190acc47073758ac3c0 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fca04cc8190a9df230078fbe268 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:37 a.m.