Triple

T942365
Position Surface form Disambiguated ID Type / Status
Subject Jens Stoltenberg E20334 entity
Predicate givenName P17 FINISHED
Object Jens
Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
E126261 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: Jens | Statement: [Jens Stoltenberg, givenName, Jens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jens
Context triple: [Jens Stoltenberg, givenName, Jens]
  • A. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • B. Niels
    Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
  • C. Johann
    Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
  • D. Jonas Lie
    Jonas Lie was a prominent Norwegian novelist and short story writer of the late 19th century, known for his realistic depictions of Norwegian society and coastal life.
  • E. Lars Jensen
    Lars Jensen is an entrepreneur best known as a co-founder of the online advertising technology company DoubleClick.
  • 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: Jens
Triple: [Jens Stoltenberg, givenName, Jens]
Generated description
Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jens
Target entity description: Jens is a masculine given name commonly used in Scandinavian and German-speaking countries, equivalent to "John" in English.
  • A. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • B. Niels
    Niels is the given name of the pioneering Norwegian mathematician Niels Henrik Abel, known for his foundational work in algebra and analysis.
  • C. Johann
    Johann is a given name of Germanic origin commonly used in German-speaking and other European countries.
  • D. Jonas Lie
    Jonas Lie was a prominent Norwegian novelist and short story writer of the late 19th century, known for his realistic depictions of Norwegian society and coastal life.
  • E. Lars Jensen
    Lars Jensen is an entrepreneur best known as a co-founder of the online advertising technology company DoubleClick.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3a1a4888190997adf56eb761431 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c017e148190b368419cff3872f6 completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4c6e67cc8190b6c491c099771fb0 completed March 7, 2026, 4:03 p.m.
NED2 Entity disambiguation (via description) batch_69ac4cfeb3c48190950c8989f49f48d8 completed March 7, 2026, 4:06 p.m.
Created at: March 1, 2026, 7:40 p.m.