Triple

T2071785
Position Surface form Disambiguated ID Type / Status
Subject Luisa E44829 entity
Predicate hasVariant P455 FINISHED
Object Lujza
Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
 E231557 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: Lujza | Statement: [Luisa, hasVariant, Lujza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lujza
Context triple: [Luisa, hasVariant, Lujza]
  • A. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • B. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • C. Ljabru
    Ljabru is a neighborhood in Oslo, Norway, known as the southeastern terminus of one of the city’s tram lines.
  • D. Liuboml
    Liuboml is a small historic town in western Ukraine near the Polish border, known for its medieval roots and multicultural heritage.
  • E. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • 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: Lujza
Triple: [Luisa, hasVariant, Lujza]
Generated description
Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lujza
Target entity description: Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
  • A. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • B. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • C. Ljabru
    Ljabru is a neighborhood in Oslo, Norway, known as the southeastern terminus of one of the city’s tram lines.
  • D. Liuboml
    Liuboml is a small historic town in western Ukraine near the Polish border, known for its medieval roots and multicultural heritage.
  • E. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0d20bc8190b19a32157f8b1607 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae272bd51881909b7da12925195417 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae28e6d8fc8190b5c0215607214b41 completed March 9, 2026, 1:56 a.m.
NED2 Entity disambiguation (via description) batch_69ae29556978819082f771e0723c4f0b completed March 9, 2026, 1:58 a.m.
Created at: March 4, 2026, 7:41 p.m.