Triple

T5011443
Position Surface form Disambiguated ID Type / Status
Subject Grauspitz E112629 entity
Predicate nearestLocality P21721 FINISHED
Object Balzers
Balzers is a municipality in southern Liechtenstein known for its scenic Alpine setting and historic Gutenberg Castle.
 E486351 NE FINISHED

How this triple was built (4 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: Balzers | Statement: [Grauspitz, nearestLocality, Balzers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Balzers
Context triple: [Grauspitz, nearestLocality, Balzers]
  • A. Vaduz
    Vaduz is the small alpine town that serves as the political and cultural center of the Principality of Liechtenstein.
  • B. Schaan
    Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Balzers
Triple: [Grauspitz, nearestLocality, Balzers]
Generated description
Balzers is a municipality in southern Liechtenstein known for its scenic Alpine setting and historic Gutenberg Castle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Balzers
Target entity description: Balzers is a municipality in southern Liechtenstein known for its scenic Alpine setting and historic Gutenberg Castle.
  • A. Vaduz
    Vaduz is the small alpine town that serves as the political and cultural center of the Principality of Liechtenstein.
  • B. Schaan
    Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
  • 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. chosen

Provenance (5 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_69bd4434acb8819086679dbeccc2fe54 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd730d70ac8190a1818d628e95ab04 completed March 20, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69be926e5ef481909df3a4b9d793300a completed March 21, 2026, 12:43 p.m.
NEDg Description generation batch_69be93efbf548190b2967a41162f2e4e completed March 21, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_69be945978a48190821103cdd306075d completed March 21, 2026, 12:51 p.m.
Created at: March 20, 2026, 1:35 p.m.