Triple

T2287270
Position Surface form Disambiguated ID Type / Status
Subject Begriffsschrift E51421 entity
Predicate placeOfPublication P1364 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: [Begriffsschrift, placeOfPublication, Halle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halle
Context triple: [Begriffsschrift, placeOfPublication, Halle]
  • A. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • B. 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.
  • C. Hanover
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • D. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • E. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc24868048190940512fd6449d99e completed March 7, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f1b2a7c8190aa836f9feba2ce1a completed March 9, 2026, 8:04 a.m.
Created at: March 4, 2026, 7:48 p.m.