Triple

T3998444
Position Surface form Disambiguated ID Type / Status
Subject Niels Torp E87153 entity
Predicate hasFamilyName P18 FINISHED
Object Torp
Torp is a Norwegian surname most notably associated with architect Niels Torp and several other prominent Norwegian families.
 E406071 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: Torp | Statement: [Niels Torp, hasFamilyName, Torp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Torp
Context triple: [Niels Torp, hasFamilyName, Torp]
  • A. Torpids
    Torpids is an annual bumps rowing competition held on the River Thames in Oxford, featuring college crews from the University of Oxford.
  • B. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • C. Corsair
    Corsair is a computer hardware and peripherals company best known for its gaming-focused products such as keyboards, mice, headsets, and PC components.
  • D. Skudai
    Skudai is a rapidly developing suburban town in the Malaysian state of Johor, known for housing Universiti Teknologi Malaysia and serving as part of the greater Johor Bahru metropolitan area.
  • E. The Trident
    The Trident is a local area or housing estate within the Palacefields district, likely forming one of its distinct residential neighbourhoods.
  • 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: Torp
Triple: [Niels Torp, hasFamilyName, Torp]
Generated description
Torp is a Norwegian surname most notably associated with architect Niels Torp and several other prominent Norwegian families.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Torp
Target entity description: Torp is a Norwegian surname most notably associated with architect Niels Torp and several other prominent Norwegian families.
  • A. Torpids
    Torpids is an annual bumps rowing competition held on the River Thames in Oxford, featuring college crews from the University of Oxford.
  • B. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • C. Corsair
    Corsair is a computer hardware and peripherals company best known for its gaming-focused products such as keyboards, mice, headsets, and PC components.
  • D. Skudai
    Skudai is a rapidly developing suburban town in the Malaysian state of Johor, known for housing Universiti Teknologi Malaysia and serving as part of the greater Johor Bahru metropolitan area.
  • E. The Trident
    The Trident is a local area or housing estate within the Palacefields district, likely forming one of its distinct residential neighbourhoods.
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa3ef7ac8190abe02f440ff83c43 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c57f60c819080e237b4b056d73b completed March 14, 2026, 11:54 a.m.
NEDg Description generation batch_69b54dbaf3d88190962e5c0b5b4604d4 completed March 14, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_69b54e16cde48190bb82f0eb04470629 completed March 14, 2026, 12:01 p.m.
Created at: March 9, 2026, 3:34 p.m.