Triple

T3967554
Position Surface form Disambiguated ID Type / Status
Subject Zlatan Ibrahimović E92251 entity
Predicate partner P1136 FINISHED
Object Helena Seger
Helena Seger is a Swedish businesswoman and former model best known as the long-term partner of footballer Zlatan Ibrahimović.
E401189 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: Helena Seger | Statement: [Zlatan Ibrahimović, partner, Helena Seger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helena Seger
Context triple: [Zlatan Ibrahimović, partner, Helena Seger]
  • A. Sara Esberg
    Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
  • B. Cecilia Nessen
    Cecilia Nessen is a film producer best known for her work on the documentary "I Am Greta," which follows climate activist Greta Thunberg.
  • C. Heléne Andersson
    Heléne Andersson is known as one of the children of Benny Andersson, the Swedish musician and composer from the pop group ABBA.
  • D. Therese Andersson
    Therese Andersson is known as the wife of former Swedish NHL star goaltender Henrik Lundqvist.
  • E. Kristina Lugn
    Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
  • 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: Helena Seger
Triple: [Zlatan Ibrahimović, partner, Helena Seger]
Generated description
Helena Seger is a Swedish businesswoman and former model best known as the long-term partner of footballer Zlatan Ibrahimović.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helena Seger
Target entity description: Helena Seger is a Swedish businesswoman and former model best known as the long-term partner of footballer Zlatan Ibrahimović.
  • A. Sara Esberg
    Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
  • B. Cecilia Nessen
    Cecilia Nessen is a film producer best known for her work on the documentary "I Am Greta," which follows climate activist Greta Thunberg.
  • C. Heléne Andersson
    Heléne Andersson is known as one of the children of Benny Andersson, the Swedish musician and composer from the pop group ABBA.
  • D. Therese Andersson
    Therese Andersson is known as the wife of former Swedish NHL star goaltender Henrik Lundqvist.
  • E. Kristina Lugn
    Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef978a14c8190a7982a2e4489b6ea completed March 9, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533c189a88190b3a81c63621b98ac completed March 14, 2026, 10:09 a.m.
NEDg Description generation batch_69b53470617c8190ab92103943c8ac7b completed March 14, 2026, 10:12 a.m.
NED2 Entity disambiguation (via description) batch_69b5352cae14819097fdf02b324fe814 completed March 14, 2026, 10:15 a.m.
Created at: March 9, 2026, 3:32 p.m.