Triple

T21542432
Position Surface form Disambiguated ID Type / Status
Subject Hondsrug area E531524 entity
Predicate hasSettlement P1068 FINISHED
Object Borger 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: Borger | Statement: [Hondsrug area, hasSettlement, Borger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borger
Context triple: [Hondsrug area, hasSettlement, Borger]
  • A. Borger
    Borger is a small industrial city in the Texas Panhandle known historically for its oil and gas production.
  • B. Borger chosen
    Borger is a village in the Dutch province of Drenthe, known for its prehistoric megalithic tombs (hunebedden) and archaeological heritage.
  • C. Borghorst
    Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
  • D. Parsberg
    Parsberg is a small Bavarian town in southeastern Germany known for its historic hilltop castle and location along major transport routes between Nuremberg and Regensburg.
  • E. Boerne
    Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
  • 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58c34808190b0eb54ba01e2cc13 completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.