Triple

T12296002
Position Surface form Disambiguated ID Type / Status
Subject West African Pidgin English E293087 entity
Predicate influenced P9 FINISHED
Object Krio E91486 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: Krio | Statement: [West African Pidgin English, influenced, Krio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krio
Context triple: [West African Pidgin English, influenced, Krio]
  • A. Krio language chosen
    Krio is an English-based creole language spoken primarily in Sierra Leone, where it serves as a major lingua franca among diverse ethnic groups.
  • B. Kennyo
    Kennyo was a 16th-century Japanese Jōdo Shinshū Buddhist monk and militant leader who headed the Ishiyama Hongan-ji fortress and resisted Oda Nobunaga’s unification efforts.
  • C. Kpelle
    Kpelle is a major Mande language spoken primarily in Liberia and Guinea by the Kpelle people.
  • D. Dili
    Dili is the coastal capital and largest city of Timor-Leste, serving as its political, economic, and cultural center.
  • E. Kankana-ey
    Kankana-ey is an Austronesian language spoken by the Kankanaey people of the northern Philippines, particularly in the Cordillera region of Luzon.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93ed903808190b7ed90e0db3d7586 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e79bf548190bf7f314222ed1ed1 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.