Triple

T18058142
Position Surface form Disambiguated ID Type / Status
Subject Tage Erlander E432094 entity
Predicate familyName P18 FINISHED
Object Erlander
Erlander is a Swedish surname most notably associated with Tage Erlander, Sweden’s long-serving mid-20th-century prime minister.
 E1304281 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: Erlander | Statement: [Tage Erlander, familyName, Erlander]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Erlander
Context triple: [Tage Erlander, familyName, Erlander]
  • A. Svene
    Svene is a small village in Flesberg Municipality in Buskerud county, Norway.
  • B. Liland
    Liland is a small village in Evenes Municipality in Nordland county, Norway, known for its scenic coastal setting in Northern Norway.
  • C. Svante
    Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
  • D. Borge
    Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
  • E. Olof
    Olof is a Scandinavian male given name, particularly common in Sweden and Norway, derived from Old Norse and borne by various notable historical and cultural figures.
  • 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: Erlander
Triple: [Tage Erlander, familyName, Erlander]
Generated description
Erlander is a Swedish surname most notably associated with Tage Erlander, Sweden’s long-serving mid-20th-century prime minister.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Erlander
Target entity description: Erlander is a Swedish surname most notably associated with Tage Erlander, Sweden’s long-serving mid-20th-century prime minister.
  • A. Svene
    Svene is a small village in Flesberg Municipality in Buskerud county, Norway.
  • B. Liland
    Liland is a small village in Evenes Municipality in Nordland county, Norway, known for its scenic coastal setting in Northern Norway.
  • C. Svante
    Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
  • D. Borge
    Borge is a district and former municipality that is now part of the city of Fredrikstad in southeastern Norway.
  • E. Olof
    Olof is a Scandinavian male given name, particularly common in Sweden and Norway, derived from Old Norse and borne by various notable historical and cultural figures.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4c1048c00819097c7dfbf76bb0987 completed April 19, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a03566907988190aef2b0ceb2c9f4dc completed May 12, 2026, 4:33 p.m.
NEDg Description generation batch_6a03591fa4cc819084d1e50b7e5263cf completed May 12, 2026, 4:45 p.m.
NED2 Entity disambiguation (via description) batch_6a0359a3ead48190996d95ad5aaa2302 completed May 12, 2026, 4:47 p.m.
Created at: April 10, 2026, 10:26 a.m.