Triple

T17987077
Position Surface form Disambiguated ID Type / Status
Subject Adrian von Bubenberg E430262 entity
Predicate controlledTerritory P16398 FINISHED
Object Spiez 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: Spiez | Statement: [Adrian von Bubenberg, controlledTerritory, Spiez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spiez
Context triple: [Adrian von Bubenberg, controlledTerritory, Spiez]
  • A. Spiez chosen
    Spiez is a picturesque Swiss town in the Bernese Oberland, known for its lakeside setting, historic castle, and views of the surrounding Alps.
  • B. Spynie
    Spynie is a small settlement in Moray, Scotland, historically associated with the nearby medieval Spynie Palace.
  • C. Spio
    Spio is a figure from Greek mythology, traditionally known as one of the Nereids, the sea nymph daughters of Nereus and Doris.
  • D. Spotnitz
    Spotnitz is a surname most notably associated with Frank Spotnitz, an American television writer and producer known for his work on series such as The X-Files.
  • E. Sciarra
    Sciarra is an Italian given name historically associated with the noble Colonna family, notably the medieval nobleman Sciarra Colonna.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b29c6d0881909d450d2561d532a6 completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.