Triple

T17736489
Position Surface form Disambiguated ID Type / Status
Subject Lidia Skoblikova E442731 entity
Predicate givenName P17 FINISHED
Object Lidia
Lidia is a feminine given name used in various cultures, notably in Slavic and Romance-speaking countries.
 E452685 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: Lidia | Statement: [Lidia Skoblikova, givenName, Lidia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lidia
Context triple: [Lidia Skoblikova, givenName, Lidia]
  • A. Lidia
    Lidia Zamenhof was a Polish Esperantist, translator, and writer, known for promoting Esperanto and translating major literary works into the language.
  • B. Lidia
    Lidia is a central character in the Spanish television series "La verdad," around whom much of the mystery and drama of the plot revolves.
  • C. Aleida
    Aleida is a feminine given name of Spanish origin, notably borne by Aleida Guevara, the daughter of revolutionary leader Che Guevara.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Marcela
    Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
  • 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: Lidia
Triple: [Lidia Skoblikova, givenName, Lidia]
Generated description
Lidia is a feminine given name used in various cultures, notably in Slavic and Romance-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lidia
Target entity description: Lidia is a feminine given name used in various cultures, notably in Slavic and Romance-speaking countries.
  • A. Lidia chosen
    Lidia Zamenhof was a Polish Esperantist, translator, and writer, known for promoting Esperanto and translating major literary works into the language.
  • B. Lidia
    Lidia is a central character in the Spanish television series "La verdad," around whom much of the mystery and drama of the plot revolves.
  • C. Aleida
    Aleida is a feminine given name of Spanish origin, notably borne by Aleida Guevara, the daughter of revolutionary leader Che Guevara.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Marcela
    Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478ec48988190a503f9aafeab6d23 completed April 19, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0242f965148190a7b76796546ab920 completed May 11, 2026, 8:58 p.m.
NEDg Description generation batch_6a02455730948190b1151d24f260d768 completed May 11, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a0245c34d008190ae029000dc8e9cbc completed May 11, 2026, 9:10 p.m.
Created at: April 10, 2026, 10:08 a.m.