Triple

T8066199
Position Surface form Disambiguated ID Type / Status
Subject District of Mittelsachsen E188248 entity
Predicate contains P35 FINISHED
Object Flöha E279933 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: Flöha | Statement: [District of Mittelsachsen, contains, Flöha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flöha
Context triple: [District of Mittelsachsen, contains, Flöha]
  • A. Flöha chosen
    Flöha is a small town in the Free State of Saxony in eastern Germany, situated near Chemnitz and known historically as a local railway and industrial hub.
  • B. Frogn
    Frogn is a coastal municipality in Viken county, Norway, known for the historic Oscarsborg Fortress in the Oslofjord.
  • C. Flen
    Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
  • D. Faleniu
    Faleniu is a village on the island of Tutuila in American Samoa, located inland not far from Pago Pago and its international airport.
  • E. Frosta
    Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
  • 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff5547c8190a7ec5958a23e302f completed March 31, 2026, 3:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63e1ed44819083ed9db6c9d7b0fd completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:26 p.m.