Triple

T910560
Position Surface form Disambiguated ID Type / Status
Subject Liechtenstein E19647 entity
Predicate largestCity P235 FINISHED
Object Schaan
Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
 E112963 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: Schaan | Statement: [Liechtenstein, largestCity, Schaan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schaan
Context triple: [Liechtenstein, largestCity, Schaan]
  • A. Dudelange
    Dudelange is a town in southern Luxembourg known as one of the country’s larger industrial and residential centers near the French border.
  • B. Sélestat
    Sélestat is a historic town in the Alsace region of northeastern France, known for its well-preserved medieval architecture and cultural heritage.
  • C. Porrentruy
    Porrentruy is a historic town in northwestern Switzerland known for its medieval castle and role as a regional center in the canton of Jura.
  • D. Bütgenbach
    Bütgenbach is a municipality in eastern Belgium’s German-speaking Community, known for its scenic lake, outdoor recreation, and proximity to the strategic Elsenborn Ridge.
  • E. Esch-sur-Alzette
    Esch-sur-Alzette is Luxembourg’s second-largest city, known as an important industrial and cultural center in the country’s south near the French border.
  • 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: Schaan
Triple: [Liechtenstein, largestCity, Schaan]
Generated description
Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schaan
Target entity description: Schaan is a major municipality in Liechtenstein known as its principal urban and industrial center.
  • A. Dudelange
    Dudelange is a town in southern Luxembourg known as one of the country’s larger industrial and residential centers near the French border.
  • B. Sélestat
    Sélestat is a historic town in the Alsace region of northeastern France, known for its well-preserved medieval architecture and cultural heritage.
  • C. Porrentruy
    Porrentruy is a historic town in northwestern Switzerland known for its medieval castle and role as a regional center in the canton of Jura.
  • D. Bütgenbach
    Bütgenbach is a municipality in eastern Belgium’s German-speaking Community, known for its scenic lake, outdoor recreation, and proximity to the strategic Elsenborn Ridge.
  • E. Esch-sur-Alzette
    Esch-sur-Alzette is Luxembourg’s second-largest city, known as an important industrial and cultural center in the country’s south near the French border.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2dca5208190bc9f17cd9dd6a98f completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac119519488190a60aca9bb425f800 completed March 7, 2026, 11:52 a.m.
NEDg Description generation batch_69ac1279e9d481908644b2e6c6bdb645 completed March 7, 2026, 11:56 a.m.
NED2 Entity disambiguation (via description) batch_69ac12fba71881909537bc73c8f6c620 completed March 7, 2026, 11:58 a.m.
Created at: March 1, 2026, 7:39 p.m.