Triple

T2809083
Position Surface form Disambiguated ID Type / Status
Subject Christmas Oratorio E54123 entity
Predicate textAuthor P2353 FINISHED
Object Picander E298349 NE FINISHED

How this triple was built (2 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: Picander | Statement: [Christmas Oratorio, textAuthor, Picander]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Picander
Context triple: [Christmas Oratorio, textAuthor, Picander]
  • A. Picander chosen
    Picander was the pen name of Christian Friedrich Henrici, an 18th-century German poet best known for writing many of Johann Sebastian Bach’s sacred and secular librettos.
  • B. José Pancetti
    José Pancetti was a prominent Brazilian modernist painter best known for his seascapes and contributions to 20th-century Brazilian art.
  • C. Palau Aguilar
    Palau Aguilar is a historic medieval palace in Barcelona’s Gothic Quarter that serves as the main building of the Picasso Museum.
  • D. Acuña
    Acuña is a Mexican border city in the state of Coahuila, located across the Rio Grande from Del Rio, Texas.
  • E. Pacho
    Pacho is a town and municipality in the Cundinamarca Department of central Colombia, known historically for its agricultural production and scenic Andean surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde3165b48190a43be5e6ad23deca completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce97c3008190a966441d719d1d1c completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.