Triple

T4872371
Position Surface form Disambiguated ID Type / Status
Subject Lidingö E109113 entity
Predicate hasTwinTown P919 FINISHED
Object Hvidovre
Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
E476077 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: Hvidovre | Statement: [Lidingö, hasTwinTown, Hvidovre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hvidovre
Context triple: [Lidingö, hasTwinTown, Hvidovre]
  • A. Valby
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • B. Ennore
    Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
  • C. Ballerup
    Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
  • D. Høje Taastrup
    Høje Taastrup is a major suburban railway and transport hub in the western part of the Copenhagen metropolitan area.
  • E. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • 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: Hvidovre
Triple: [Lidingö, hasTwinTown, Hvidovre]
Generated description
Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hvidovre
Target entity description: Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
  • A. Valby
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • B. Ennore
    Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
  • C. Ballerup
    Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
  • D. Høje Taastrup
    Høje Taastrup is a major suburban railway and transport hub in the western part of the Copenhagen metropolitan area.
  • E. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d9e27908190a0c4540ee2559c4b completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67f1ca1881909a7412087fa0efab completed March 21, 2026, 9:42 a.m.
NEDg Description generation batch_69be68b9300c8190ba829be08e520047 completed March 21, 2026, 9:45 a.m.
NED2 Entity disambiguation (via description) batch_69be6961d8688190a041e476e082ac36 completed March 21, 2026, 9:48 a.m.
Created at: March 20, 2026, 1:27 p.m.