Triple

T2695742
Position Surface form Disambiguated ID Type / Status
Subject Espoo E58506 entity
Predicate hasShoppingCentre P4285 FINISHED
Object Iso Omena
Iso Omena is a large shopping and services center in Espoo, Finland, featuring a wide range of retail stores, restaurants, and public services.
E290452 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: Iso Omena | Statement: [Espoo, hasShoppingCentre, Iso Omena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iso Omena
Context triple: [Espoo, hasShoppingCentre, Iso Omena]
  • A. Vilailuck Teigen
    Vilailuck Teigen is a Thai-American television personality and social media figure best known as the mother of model and author Chrissy Teigen.
  • B. Sakari
    Sakari is a Finnish given name commonly used for males, derived from the biblical name Zachary.
  • C. Einar
    Einar is a masculine given name of Norse origin commonly used in Scandinavian countries.
  • D. Kukkonen
    Kukkonen is a Finnish surname most notably associated with Greta Kukkonen, the first wife of U.S. President Ronald Reagan.
  • E. Halvdan Koht
    Halvdan Koht was a prominent Norwegian historian, politician, and former foreign minister known for his influential role in early 20th-century Norwegian academic and political life.
  • 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: Iso Omena
Triple: [Espoo, hasShoppingCentre, Iso Omena]
Generated description
Iso Omena is a large shopping and services center in Espoo, Finland, featuring a wide range of retail stores, restaurants, and public services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Iso Omena
Target entity description: Iso Omena is a large shopping and services center in Espoo, Finland, featuring a wide range of retail stores, restaurants, and public services.
  • A. Vilailuck Teigen
    Vilailuck Teigen is a Thai-American television personality and social media figure best known as the mother of model and author Chrissy Teigen.
  • B. Sakari
    Sakari is a Finnish given name commonly used for males, derived from the biblical name Zachary.
  • C. Einar
    Einar is a masculine given name of Norse origin commonly used in Scandinavian countries.
  • D. Kukkonen
    Kukkonen is a Finnish surname most notably associated with Greta Kukkonen, the first wife of U.S. President Ronald Reagan.
  • E. Halvdan Koht
    Halvdan Koht was a prominent Norwegian historian, politician, and former foreign minister known for his influential role in early 20th-century Norwegian academic and political life.
  • 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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda2f7bf88190a1e3103dd014d871 completed March 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf6aa78c8190b57be36042008361 completed March 10, 2026, 5:43 a.m.
NEDg Description generation batch_69afb01b48508190a9b668a7273ad422 completed March 10, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69afb09133788190862d4b24d77facc0 completed March 10, 2026, 5:48 a.m.
Created at: March 6, 2026, 9:55 p.m.