Triple

T2984232
Position Surface form Disambiguated ID Type / Status
Subject Jorge Semprún E80583 entity
Predicate familyName P18 FINISHED
Object Semprún
Semprún is the surname of Jorge Semprún, the Spanish-born writer, politician, and Holocaust survivor known for his works on exile, memory, and totalitarianism.
 E317947 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: Semprún | Statement: [Jorge Semprún, familyName, Semprún]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Semprún
Context triple: [Jorge Semprún, familyName, Semprún]
  • A. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • B. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • C. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • D. Aranzazu
    Aranzazu is a small Colombian town located in the mountainous coffee-growing region of the Caldas Department.
  • E. Majadahonda
    Majadahonda is a suburban municipality west of Madrid, Spain, known for its residential character, shopping centers, and sports facilities.
  • 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: Semprún
Triple: [Jorge Semprún, familyName, Semprún]
Generated description
Semprún is the surname of Jorge Semprún, the Spanish-born writer, politician, and Holocaust survivor known for his works on exile, memory, and totalitarianism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Semprún
Target entity description: Semprún is the surname of Jorge Semprún, the Spanish-born writer, politician, and Holocaust survivor known for his works on exile, memory, and totalitarianism.
  • A. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • B. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • C. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • D. Aranzazu
    Aranzazu is a small Colombian town located in the mountainous coffee-growing region of the Caldas Department.
  • E. Majadahonda
    Majadahonda is a suburban municipality west of Madrid, Spain, known for its residential character, shopping centers, and sports facilities.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c481fc81909971c96352a881b4 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e31a8188190bd5ad6c9757e7141 completed March 11, 2026, 8:56 a.m.
NEDg Description generation batch_69b131fc55f88190a6220816f39e7d20 completed March 11, 2026, 9:12 a.m.
NED2 Entity disambiguation (via description) batch_69b1c821b31081908cfa7273a7055188 completed March 11, 2026, 7:53 p.m.
Created at: March 8, 2026, 2:59 p.m.