Triple

T12913972
Position Surface form Disambiguated ID Type / Status
Subject Letov Š-328 E308929 entity
Predicate manufacturer P490 FINISHED
Object Letov
Letov was a Czechoslovak aircraft manufacturer known for producing military and training airplanes in the interwar and World War II periods.
E1010082 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: Letov | Statement: [Letov Š-328, manufacturer, Letov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Letov
Context triple: [Letov Š-328, manufacturer, Letov]
  • A. Letkov
    Letkov is a small municipality and village in the Plzeň Region of the Czech Republic.
  • B. Lestkov
    Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
  • C. Lennik
    Lennik is a municipality in the Flemish Brabant province of Belgium, known for its rural character and historic castle of Gaasbeek.
  • D. Leova
    Leova is a small town in southwestern Moldova known for its location near the border with Romania and its position along the Prut River.
  • E. Lukin
    Lukin is a component or module associated with the "No Code" system, likely serving as a distinct functional part within that broader platform.
  • 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: Letov
Triple: [Letov Š-328, manufacturer, Letov]
Generated description
Letov was a Czechoslovak aircraft manufacturer known for producing military and training airplanes in the interwar and World War II periods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Letov
Target entity description: Letov was a Czechoslovak aircraft manufacturer known for producing military and training airplanes in the interwar and World War II periods.
  • A. Letkov
    Letkov is a small municipality and village in the Plzeň Region of the Czech Republic.
  • B. Lestkov
    Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
  • C. Lennik
    Lennik is a municipality in the Flemish Brabant province of Belgium, known for its rural character and historic castle of Gaasbeek.
  • D. Leova
    Leova is a small town in southwestern Moldova known for its location near the border with Romania and its position along the Prut River.
  • E. Lukin
    Lukin is a component or module associated with the "No Code" system, likely serving as a distinct functional part within that broader platform.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971a0d6508190bca9668e9e06abfe completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a56ea03c819093a5b8657e27768e completed May 3, 2026, 1:31 a.m.
NEDg Description generation batch_69f6a68978008190a9d8695b09a8cb3a completed May 3, 2026, 1:36 a.m.
NED2 Entity disambiguation (via description) batch_69f6a8a31264819082c1ce67eaa529cc completed May 3, 2026, 1:45 a.m.
Created at: April 9, 2026, 5:41 p.m.