Triple

T8432148
Position Surface form Disambiguated ID Type / Status
Subject Neša E199137 entity
Predicate alternativeName P39 FINISHED
Object Nesha
Nesha is a given name that can refer to various people or entities, often used as a feminine personal name in different cultures.
 E732785 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: Nesha | Statement: [Neša, alternativeName, Nesha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nesha
Context triple: [Neša, alternativeName, Nesha]
  • A. Keisha
    Keisha is a feminine given name used in English-speaking communities, often associated with African-American culture.
  • B. Nenê
    Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
  • C. Dameisha
    Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
  • D. Nikkiya
    Nikkiya is an American singer and rapper known for her collaborations in hip-hop and R&B, particularly with producer and artist K.E. on the Track (Keys).
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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: Nesha
Triple: [Neša, alternativeName, Nesha]
Generated description
Nesha is a given name that can refer to various people or entities, often used as a feminine personal name in different cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nesha
Target entity description: Nesha is a given name that can refer to various people or entities, often used as a feminine personal name in different cultures.
  • A. Keisha
    Keisha is a feminine given name used in English-speaking communities, often associated with African-American culture.
  • B. Nenê
    Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
  • C. Dameisha
    Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
  • D. Nikkiya
    Nikkiya is an American singer and rapper known for her collaborations in hip-hop and R&B, particularly with producer and artist K.E. on the Track (Keys).
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a5d7488190842e246444fc9a4e completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce038902308190bff57c9ce14e72ed completed April 2, 2026, 5:50 a.m.
NEDg Description generation batch_69ce07851c4081909a9468a386035bb2 completed April 2, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69ce07ec00248190bb10fee54265c7f9 completed April 2, 2026, 6:08 a.m.
Created at: March 30, 2026, 6:07 p.m.