Triple

T16685925
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Eduard Weber E405460 entity
Predicate workLocation P7 FINISHED
Object Halle E94413 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: Halle | Statement: [Wilhelm Eduard Weber, workLocation, Halle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halle
Context triple: [Wilhelm Eduard Weber, workLocation, Halle]
  • A. Halle
    Halle is a historic city in the Belgian province of Flemish Brabant, known for its medieval architecture and the Basilica of Saint Martin, a notable pilgrimage site.
  • B. Halle
    Halle is a feminine given name used in various cultures, notably borne by American actress and singer Halle Bailey.
  • C. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • D. Halle (Saale) chosen
    Halle (Saale) is a major city in the German state of Saxony-Anhalt, known as an important economic, cultural, and educational center, including being home to the Martin Luther University of Halle-Wittenberg.
  • E. Blentheim
    Blentheim is a location in New Zealand that serves as one of the seats of the High Court of New Zealand.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea550c0819085bd36c44237a61a completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a43f6a08190913ca123a2377f95 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.