Triple

T6592880
Position Surface form Disambiguated ID Type / Status
Subject Bangui E148403 entity
Predicate officialLanguage P236 FINISHED
Object Sango E274564 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: Sango | Statement: [Bangui, officialLanguage, Sango]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sango
Context triple: [Bangui, officialLanguage, Sango]
  • A. Sango chosen
    Sango is a Central African lingua franca and national language of the Central African Republic, originating as a Ngbandi-based trade language.
  • B. Tanno
    Tanno is a district or locality within the city of Kitami in Hokkaido, Japan.
  • C. Ogunai
    Ogunai is a small riverside settlement located along the Fly River in Papua New Guinea.
  • D. Shingu
    Shingu is a coastal city in Japan known for its historic Kumano Hongu Taisha shrine and its role as a gateway to the sacred Kumano Kodo pilgrimage routes.
  • E. Nakanamanga
    Nakanamanga is an Oceanic Austronesian language spoken primarily on Efate Island and nearby areas in Vanuatu.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aecf50ac81909cb9960c8265a7ea completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d57d338c81909e935926d635d2fc completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:55 p.m.