Triple

T18622843
Position Surface form Disambiguated ID Type / Status
Subject Bogusław Linda E455198 entity
Predicate notableWork P4 FINISHED
Object Tato
Tato is a Polish drama film best known for starring acclaimed actor Bogusław Linda as a father fighting for custody of his daughter.
E1334891 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: Tato | Statement: [Bogusław Linda, notableWork, Tato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tato
Context triple: [Bogusław Linda, notableWork, Tato]
  • A. Tato
    Tato was an early Lombard king of the Lething dynasty, known from tradition as a pre-migration ruler in the tribe’s legendary history.
  • B. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • C. Otomí
    Otomí is an indigenous people of central Mexico whose Oto-Manguean language and rich cultural traditions have persisted since pre-Hispanic times.
  • D. Jínova
    Jínova is a municipal district within the municipality of San Juan de la Maguana in the San Juan Province of the Dominican Republic.
  • E. Mže
    Mže is a river in the Czech Republic that flows through the city of Plzeň and forms part of the Berounka river system.
  • 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: Tato
Triple: [Bogusław Linda, notableWork, Tato]
Generated description
Tato is a Polish drama film best known for starring acclaimed actor Bogusław Linda as a father fighting for custody of his daughter.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tato
Target entity description: Tato is a Polish drama film best known for starring acclaimed actor Bogusław Linda as a father fighting for custody of his daughter.
  • A. Tato
    Tato was an early Lombard king of the Lething dynasty, known from tradition as a pre-migration ruler in the tribe’s legendary history.
  • B. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • C. Otomí
    Otomí is an indigenous people of central Mexico whose Oto-Manguean language and rich cultural traditions have persisted since pre-Hispanic times.
  • D. Jínova
    Jínova is a municipal district within the municipality of San Juan de la Maguana in the San Juan Province of the Dominican Republic.
  • E. Mže
    Mže is a river in the Czech Republic that flows through the city of Plzeň and forms part of the Berounka river system.
  • 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54f020fa08190bd78d72182496b19 completed April 19, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a050d765bb081908aab41aa6bb97fe4 completed May 13, 2026, 11:47 p.m.
NEDg Description generation batch_6a050f6306ac8190aa4d72627345cf55 completed May 13, 2026, 11:55 p.m.
NED2 Entity disambiguation (via description) batch_6a050ff68a7c8190bf82d00370f4b1d4 completed May 13, 2026, 11:57 p.m.
Created at: April 10, 2026, 11:46 a.m.