Triple

T19838109
Position Surface form Disambiguated ID Type / Status
Subject Kelp gull E476651 entity
Predicate describedBy P264 FINISHED
Object Lichtenstein NE NERFINISHED

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: Lichtenstein | Statement: [Kelp gull, describedBy, Lichtenstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lichtenstein
Context triple: [Kelp gull, describedBy, Lichtenstein]
  • A. Lichtenstein
    Lichtenstein is a municipality in the district of Reutlingen in the German state of Baden-Württemberg, known for the nearby Lichtenstein Castle.
  • B. Lichtenstein chosen
    Lichtenstein is a surname most famously associated with Roy Lichtenstein, the American pop artist known for his comic-strip-inspired paintings.
  • C. Luxembourg
    Luxembourg is a small, landlocked Western European country known for its prosperous economy, status as a major financial center, and role as a founding member of the European Union.
  • D. Luxemburg
    Luxemburg is a surname most famously associated with Rosa Luxemburg, the Marxist theorist, revolutionary socialist, and co-founder of the Spartacist League in Germany.
  • E. Liechtenstein
    Liechtenstein is a small, landlocked principality in Central Europe known for its alpine landscape, strong financial sector, and status as one of the world's wealthiest countries per capita.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65803bb988190a4e7c0035058feba completed April 20, 2026, 4:44 p.m.
Created at: April 10, 2026, 1:50 p.m.