Triple

T21433390
Position Surface form Disambiguated ID Type / Status
Subject August Bebel E528745 entity
Predicate has part in the series P68494 FINISHED
Object history of the German labour movement LITERAL 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: history of the German labour movement | Statement: [August Bebel, has part in the series, history of the German labour movement]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: has part in the series
Context triple: [August Bebel, has part in the series, history of the German labour movement]
  • A. has part in role
    Indicates that an entity participates as a component or constituent specifically in a defined role within a larger whole or process.
  • B. partOfSeriesWith chosen
    Indicates that one entity is a member or installment within the same series as another entity, linking them as related parts of a larger sequence or collection.
  • C. hasPartInFilmSeries
    Indicates that an entity participates in or contributes to one or more installments within a specific film series.
  • D. worksInSeriesWith
    Indicates that one entity collaborates or participates together with another entity within the same series or serialized work.
  • E. hasPartInTrilogy
    Indicates that an entity is one of the constituent parts (e.g., books, films, or episodes) that together form a specific trilogy.
  • F. None of above.

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_69e0c4569fa081908101baa24f8745db completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee813fe2108190a4193f69667fe79e completed April 26, 2026, 9:18 p.m.
PD Predicate disambiguation batch_69e61639ee288190889ffd500d1260f6 completed April 20, 2026, 12:04 p.m.
Created at: April 16, 2026, 5:59 p.m.