Triple

T11475326
Position Surface form Disambiguated ID Type / Status
Subject House of Ascania E272011 entity
Predicate hasMainTerritory P1103 FINISHED
Object Lauenburg E155306 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: Lauenburg | Statement: [House of Ascania, hasMainTerritory, Lauenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauenburg
Context triple: [House of Ascania, hasMainTerritory, Lauenburg]
  • A. Lauenburg chosen
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • B. Güstrow
    Güstrow is a historic town in northern Germany known for its Renaissance castle, brick Gothic cathedral, and association with sculptor Ernst Barlach.
  • C. Himmerich
    Himmerich is a hill in Germany’s Siebengebirge range, known for its forested slopes and hiking trails overlooking the Rhine valley.
  • D. Lübstorf
    Lübstorf is a small municipality in northern Germany’s Mecklenburg-Vorpommern state, situated near Lake Schwerin and characterized by its rural setting and natural surroundings.
  • E. Glücksburg
    Glücksburg is a European royal house of German origin that has provided monarchs to several countries, including Denmark, Norway, and Greece.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294c8dc48190a515f83c99405a3b completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6249ee74881908814cf59c82038a6 completed April 20, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:36 p.m.