Triple

T5261552
Position Surface form Disambiguated ID Type / Status
Subject Varig E118834 entity
Predicate ownedBrand P1500 FINISHED
Object VarigLog
VarigLog was a Brazilian cargo airline and logistics company that operated freight services domestically and internationally, originally linked to the former national carrier Varig.
 E118834 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: VarigLog | Statement: [Varig, ownedBrand, VarigLog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VarigLog
Context triple: [Varig, ownedBrand, VarigLog]
  • A. Varig
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • B. LOG
    LOG is the ICAO airline designator assigned to Loganair, a regional airline based in Scotland.
  • C. Logierait
    Logierait is a small village in Perth and Kinross, Scotland, known as the birthplace of the philosopher and historian Adam Ferguson.
  • D. Varvarin
    Varvarin is a small town in central Serbia situated on the banks of the Velika Morava River.
  • E. Logres
    Logres is the legendary kingdom associated with King Arthur, often depicted as the idealized realm of Camelot and the Knights of the Round Table in Arthurian romance.
  • 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: VarigLog
Triple: [Varig, ownedBrand, VarigLog]
Generated description
VarigLog was a Brazilian cargo airline and logistics company that operated freight services domestically and internationally, originally linked to the former national carrier Varig.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VarigLog
Target entity description: VarigLog was a Brazilian cargo airline and logistics company that operated freight services domestically and internationally, originally linked to the former national carrier Varig.
  • A. Varig chosen
    Varig was Brazil’s former flagship airline, once the country’s largest carrier and a major international operator throughout much of the 20th century.
  • B. LOG
    LOG is the ICAO airline designator assigned to Loganair, a regional airline based in Scotland.
  • C. Logierait
    Logierait is a small village in Perth and Kinross, Scotland, known as the birthplace of the philosopher and historian Adam Ferguson.
  • D. Varvarin
    Varvarin is a small town in central Serbia situated on the banks of the Velika Morava River.
  • E. Logres
    Logres is the legendary kingdom associated with King Arthur, often depicted as the idealized realm of Camelot and the Knights of the Round Table in Arthurian romance.
  • 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_69bd446a42c88190b7ecbef006561d55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7bd0c5f48190a1be89314c59f96b completed March 20, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe85a3f88190ae014b18b1df202e completed March 21, 2026, 8:24 p.m.
NEDg Description generation batch_69beff56b42881909ff4f574ef87b693 completed March 21, 2026, 8:28 p.m.
NED2 Entity disambiguation (via description) batch_69bf00120fe88190817badb72977566e completed March 21, 2026, 8:31 p.m.
Created at: March 20, 2026, 1:50 p.m.