Triple

T12971627
Position Surface form Disambiguated ID Type / Status
Subject Hesse-Nassau E321410 entity
Predicate contains P35 FINISHED
Object Hersfeld E854969 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: Hersfeld | Statement: [Hesse-Nassau, contains, Hersfeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hersfeld
Context triple: [Hesse-Nassau, contains, Hersfeld]
  • A. Hersfeld-Rotenburg chosen
    Hersfeld-Rotenburg is a rural district in eastern Hesse, Germany, known for its historic towns, forests, and location along the Fulda River.
  • B. Filderstadt
    Filderstadt is a town in the German state of Baden-Württemberg, situated just south of Stuttgart and known for its proximity to Stuttgart Airport and role as a regional transport hub.
  • C. Suhl
    Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
  • D. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • E. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e418d548190be1c73db76cb3aa8 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75469a3f08190a7e417872147b455 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 8:36 p.m.