Triple

T12190569
Position Surface form Disambiguated ID Type / Status
Subject Tietoevry E290449 entity
Predicate formerName P65 FINISHED
Object EVRY
EVRY was a major Nordic IT services and software company that later merged with Tieto to form Tietoevry.
 E964473 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: EVRY | Statement: [Tietoevry, formerName, EVRY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EVRY
Context triple: [Tietoevry, formerName, EVRY]
  • A. Evvy
    Evvy is a given name typically used as a short or affectionate form of longer names such as Evan or Evelyn.
  • B. Marmon Retail Solutions
    Marmon Retail Solutions is a business unit within the Marmon Group that provides equipment, fixtures, and integrated solutions for the retail industry.
  • C. Ventra
    Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
  • D. Geralds
    Geralds is a village on the Caribbean island of Montserrat, known for hosting the island’s main airport.
  • E. Fauske
    Fauske is a small Norwegian town and municipality known for its marble quarries and location in the inland part of Nordland county.
  • 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: EVRY
Triple: [Tietoevry, formerName, EVRY]
Generated description
EVRY was a major Nordic IT services and software company that later merged with Tieto to form Tietoevry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EVRY
Target entity description: EVRY was a major Nordic IT services and software company that later merged with Tieto to form Tietoevry.
  • A. Evvy
    Evvy is a given name typically used as a short or affectionate form of longer names such as Evan or Evelyn.
  • B. Marmon Retail Solutions
    Marmon Retail Solutions is a business unit within the Marmon Group that provides equipment, fixtures, and integrated solutions for the retail industry.
  • C. Ventra
    Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
  • D. Geralds
    Geralds is a village on the Caribbean island of Montserrat, known for hosting the island’s main airport.
  • E. Fauske
    Fauske is a small Norwegian town and municipality known for its marble quarries and location in the inland part of Nordland county.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c5340248190b79379423f3a3ca1 completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6b240f88190af916054869c3b95 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f5ff826ea08190a6780351e4b927ac completed May 2, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_69f60185ce8c8190abe3b1f633aac55d completed May 2, 2026, 1:52 p.m.
Created at: April 8, 2026, 9:50 p.m.