Triple

T5734599
Position Surface form Disambiguated ID Type / Status
Subject Merseburg, East Germany E126468 entity
Predicate near P350 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: [Merseburg, East Germany, near, Halle (Saale)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halle (Saale)
Context triple: [Merseburg, East Germany, near, 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. 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.
  • C. Halle
    Halle is a surname most notably borne by Morris Halle, a prominent linguist and phonologist.
  • D. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • E. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02536706c8190a69665b75c8a38e9 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e05a7e08190a79fb43aefdbea6b completed March 22, 2026, 11:40 p.m.
Created at: March 22, 2026, 3:47 p.m.