Triple

T3497187
Position Surface form Disambiguated ID Type / Status
Subject Nicolás Guillén E73878 entity
Predicate notableWork P4 FINISHED
Object Sóngoro cosongo E68546 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: Sóngoro cosongo | Statement: [Nicolás Guillén, notableWork, Sóngoro cosongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sóngoro cosongo
Context triple: [Nicolás Guillén, notableWork, Sóngoro cosongo]
  • A. Sóngoro cosongo chosen
    Sóngoro cosongo is a landmark 1931 poetry collection by Cuban writer Nicolás Guillén that blends Afro-Cuban rhythms, vernacular language, and social commentary to celebrate Black Cuban culture.
  • B. Songo
    Songo is a small town in Mozambique known primarily for its proximity to the Cahora Bassa Dam and its role in supporting the dam’s operations and nearby communities.
  • C. Somosomo
    Somosomo is a coastal village on the Fijian island of Taveuni, known as a traditional center of chiefly authority and local administration.
  • D. Kisolongo
    Kisolongo is a regional dialect of the Kikongo language spoken by Kongo communities in parts of Central Africa.
  • E. Sgonico
    Sgonico is a small municipality in northeastern Italy, situated on the Karst Plateau near Trieste and known for its natural caves and rural landscape.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd16c0081908f13535f459618d1 completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373d011c0819088245afe03be3c44 completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:18 p.m.