Triple

T18115809
Position Surface form Disambiguated ID Type / Status
Subject Oberpfalz E433601 entity
Predicate contains P35 FINISHED
Object Cham (district) NE NERFINISHED

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: Cham (district) | Statement: [Oberpfalz, contains, Cham (district)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cham (district)
Context triple: [Oberpfalz, contains, Cham (district)]
  • A. Cham (district) chosen
    Cham (district) is a rural administrative district in eastern Bavaria, Germany, bordering the Czech Republic and known for its forests, river valleys, and small towns.
  • B. Cham District
    Cham District is an administrative district in the Upper Palatinate region of Bavaria, Germany, known for its location along the Czech border and its mix of rural landscapes and small towns.
  • C. Tutak District
    Tutak District is an administrative district located within Turkey’s eastern Ağrı Province, known for its rural settlements and mountainous terrain.
  • D. Hanang District
    Hanang District is an administrative district in northern Tanzania known for its agricultural communities and the prominent Mount Hanang.
  • E. Maran District
    Maran District is an administrative district in the state of Pahang, Malaysia, known for its rural landscape and agricultural activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddd58ea8819081e2bec5e591e093 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.