Triple

T11875560
Position Surface form Disambiguated ID Type / Status
Subject Johann Salomo Semler E282516 entity
Predicate workLocation P7 FINISHED
Object Halle (Saale) 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 (Saale) | Statement: [Johann Salomo Semler, workLocation, Halle (Saale)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halle (Saale)
Context triple: [Johann Salomo Semler, workLocation, Halle (Saale)]
  • A. 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.
  • B. Haldensleben
    Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
  • C. Sangerhausen
    Sangerhausen is a town in the German state of Saxony-Anhalt, known for its historic mining heritage and its renowned Europa-Rosarium rose garden.
  • D. Halle
    Halle is a feminine given name used in various cultures, notably borne by American actress and singer Halle Bailey.
  • E. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1a22448190bd0722188c14d7bd completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417cb1c3881909ee50e8d11621664 completed May 1, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:44 p.m.