Triple

T17156913
Position Surface form Disambiguated ID Type / Status
Subject Polikarpov I-15 E416364 entity
Predicate nickName P2937 FINISHED
Object Chato
Chato was the popular nickname for the Soviet Polikarpov I-15 biplane fighter, widely used during the Spanish Civil War.
 E1258238 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: Chato | Statement: [Polikarpov I-15, nickName, Chato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Chato
Context triple: [Polikarpov I-15, nickName, Chato]
  • A. Mocorito
    Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
  • B. Chacala
    Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
  • C. Chaguanas
    Chaguanas is a rapidly growing commercial and residential hub on the island of Trinidad, known for its bustling markets and diverse population.
  • D. Choachí
    Choachí is a mountainous municipality in the Cundinamarca Department of Colombia, known for its cool climate, natural landscapes, and proximity to Bogotá.
  • E. Lozoya
    Lozoya is a small municipality in the Sierra Norte region of the Community of Madrid, Spain, known for its mountainous landscapes and proximity to the Lozoya River.
  • 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: Chato
Triple: [Polikarpov I-15, nickName, Chato]
Generated description
Chato was the popular nickname for the Soviet Polikarpov I-15 biplane fighter, widely used during the Spanish Civil War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Chato
Target entity description: Chato was the popular nickname for the Soviet Polikarpov I-15 biplane fighter, widely used during the Spanish Civil War.
  • A. Mocorito
    Mocorito is a historic town and municipality in the Mexican state of Sinaloa, known for its colonial architecture and cultural traditions.
  • B. Chacala
    Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
  • C. Chaguanas
    Chaguanas is a rapidly growing commercial and residential hub on the island of Trinidad, known for its bustling markets and diverse population.
  • D. Choachí
    Choachí is a mountainous municipality in the Cundinamarca Department of Colombia, known for its cool climate, natural landscapes, and proximity to Bogotá.
  • E. Lozoya
    Lozoya is a small municipality in the Sierra Norte region of the Community of Madrid, Spain, known for its mountainous landscapes and proximity to the Lozoya River.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f40bf9ec8190b16372bcd091db9b completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a016745f32c81909499f71920e8babe completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a016bcdd19c81909fe5ffcc57c7c4d1 completed May 11, 2026, 5:40 a.m.
NED2 Entity disambiguation (via description) batch_6a016c5018e48190974c124c3433bcc6 completed May 11, 2026, 5:42 a.m.
Created at: April 10, 2026, 5:37 a.m.