Triple

T3232194
Position Surface form Disambiguated ID Type / Status
Subject Henrik E67764 entity
Predicate hasVariant P455 FINISHED
Object Henrikas
Henrikas is a Lithuanian given name, corresponding to the name Henrik or Henry in other languages.
 E67764 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: Henrikas | Statement: [Henrik, hasVariant, Henrikas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henrikas
Context triple: [Henrik, hasVariant, Henrikas]
  • A. Henrik
    Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
  • B. Waldemar
    Waldemar is a masculine given name of Germanic origin, historically associated with Scandinavian and Central European nobility and notable figures.
  • C. Henricus
    Henricus was an early 17th-century English colonial settlement in Virginia, established as one of the first permanent towns in North America.
  • D. Ludvig
    Ludvig is a given name, primarily used in Scandinavian countries, that is a variant spelling of Ludwig.
  • E. 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.
  • 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: Henrikas
Triple: [Henrik, hasVariant, Henrikas]
Generated description
Henrikas is a Lithuanian given name, corresponding to the name Henrik or Henry in other languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henrikas
Target entity description: Henrikas is a Lithuanian given name, corresponding to the name Henrik or Henry in other languages.
  • A. Henrik chosen
    Henrik is the given name of the renowned Norwegian mathematician Niels Henrik Abel, known for his pioneering work in algebra and analysis.
  • B. Waldemar
    Waldemar is a masculine given name of Germanic origin, historically associated with Scandinavian and Central European nobility and notable figures.
  • C. Henricus
    Henricus was an early 17th-century English colonial settlement in Virginia, established as one of the first permanent towns in North America.
  • D. Ludvig
    Ludvig is a given name, primarily used in Scandinavian countries, that is a variant spelling of Ludwig.
  • E. 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.
  • F. None of above.

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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaed99d2c8190950fa883ec6f1f8e completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28e9f56b881908742f2aff68b2a34 completed March 12, 2026, 9:59 a.m.
NEDg Description generation batch_69b2966f189c8190bb56daea54be8a93 completed March 12, 2026, 10:33 a.m.
NED2 Entity disambiguation (via description) batch_69b2d6bf36988190b394766e9821047c completed March 12, 2026, 3:07 p.m.
Created at: March 8, 2026, 3:08 p.m.