Triple

T11272727
Position Surface form Disambiguated ID Type / Status
Subject Selhof E266852 entity
Predicate adjacentTo P224 FINISHED
Object Aegidienberg E266851 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: Aegidienberg | Statement: [Selhof, adjacentTo, Aegidienberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aegidienberg
Context triple: [Selhof, adjacentTo, Aegidienberg]
  • A. Aegidienberg chosen
    Aegidienberg is a district of the town of Bad Honnef in North Rhine-Westphalia, Germany, known for its scenic location in the Siebengebirge region.
  • B. Festungsberg
    Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
  • C. Oberhalbstein
    Oberhalbstein is a high Alpine valley and region in the canton of Graubünden, Switzerland, known for its Romansh-speaking communities and mountain landscapes.
  • D. Witzmannsberg
    Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
  • E. Erzhausen
    Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58af8bc988190805168188ed0a6aa completed April 20, 2026, 2:10 a.m.
Created at: April 8, 2026, 9:31 p.m.