Triple

T8859169
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Heidenheim E210840 entity
Predicate hasRiver P165 FINISHED
Object Brenz E111222 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: Brenz | Statement: [Landkreis Heidenheim, hasRiver, Brenz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brenz
Context triple: [Landkreis Heidenheim, hasRiver, Brenz]
  • A. Brenz chosen
    The Brenz is a river in southern Germany that flows through Baden-Württemberg and Bavaria before joining the Danube.
  • B. Brenner
    Brenner is a surname of German origin borne by various notable individuals across fields such as science, politics, and the arts.
  • C. BREN-don
    BREN-don is the stressed syllable pattern of the English given name "Brendon," indicating primary stress on the first syllable.
  • D. Breng
    Breng is a Dutch public transport operator providing regional bus and train services in and around Arnhem and Nijmegen in the Netherlands.
  • E. Blye
    Blye is the surname of Kensi Blye, a central character and special agent on the television series "NCIS: Los Angeles."
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e536648190ba8da1375478c24f completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0b1b86481909ec0b78de043d8f8 completed April 3, 2026, 11:12 a.m.
Created at: March 30, 2026, 6:50 p.m.