Triple

T4517387
Position Surface form Disambiguated ID Type / Status
Subject Solitaire E103183 entity
Predicate antagonistTo P18963 FINISHED
Object Kananga E449098 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: Kananga | Statement: [Solitaire, antagonistTo, Kananga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kananga
Context triple: [Solitaire, antagonistTo, Kananga]
  • A. Kananga chosen
    Kananga is the primary antagonist and Caribbean dictator in the James Bond film "Live and Let Die," who operates under the alias Mr. Big as a powerful drug lord.
  • B. Gokwe
    Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
  • C. Chilombo
    Chilombo is the surname of American R&B singer and songwriter Jhené Aiko, reflecting her mixed Japanese, African American, and Native American heritage.
  • D. Karanga
    Karanga is a major dialect of the Shona language spoken primarily in southern Zimbabwe, known for its distinct phonological and lexical features.
  • E. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • 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_69bd43dba59881908cf59b31df8c7ae1 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd572933408190b67c4ef6a7babe75 completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda42bd41c8190a9a25ccea6947089 completed March 20, 2026, 7:46 p.m.
Created at: March 20, 2026, 1:02 p.m.