Triple

T15945500
Position Surface form Disambiguated ID Type / Status
Subject Kambaata language E386672 entity
Predicate hasDialect P4251 FINISHED
Object Tambaro
Tambaro is a dialect of the Kambaata language spoken by a community in southern Ethiopia.
 E1185260 NE FINISHED

How this triple was built (4 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: Tambaro | Statement: [Kambaata language, hasDialect, Tambaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tambaro
Context triple: [Kambaata language, hasDialect, Tambaro]
  • A. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • B. Taburao
    Taburao is a village on the atoll of Abaiang in the island nation of Kiribati.
  • C. Tokoro
    Tokoro is a coastal district of Kitami City in Hokkaido, Japan, known historically for its fishing industry and drift ice along the Sea of Okhotsk.
  • D. Mararaba
    Mararaba is a rapidly growing suburban town near Abuja in central Nigeria, known for its dense population and heavy commuter traffic.
  • E. Itaboraí
    Itaboraí is a municipality in the state of Rio de Janeiro, Brazil, known for its industrial development and proximity to the metropolitan area of Rio de Janeiro.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tambaro
Triple: [Kambaata language, hasDialect, Tambaro]
Generated description
Tambaro is a dialect of the Kambaata language spoken by a community in southern Ethiopia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tambaro
Target entity description: Tambaro is a dialect of the Kambaata language spoken by a community in southern Ethiopia.
  • A. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • B. Taburao
    Taburao is a village on the atoll of Abaiang in the island nation of Kiribati.
  • C. Tokoro
    Tokoro is a coastal district of Kitami City in Hokkaido, Japan, known historically for its fishing industry and drift ice along the Sea of Okhotsk.
  • D. Mararaba
    Mararaba is a rapidly growing suburban town near Abuja in central Nigeria, known for its dense population and heavy commuter traffic.
  • E. Itaboraí
    Itaboraí is a municipality in the state of Rio de Janeiro, Brazil, known for its industrial development and proximity to the metropolitan area of Rio de Janeiro.
  • F. None of above. chosen

Provenance (5 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156d0d55c8190af59ff169e8add78 completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5beabbc8190977f14c1b3ccdf29 completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb677927c8190bd45e7bae5fcf1ed completed May 9, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7468fb88190a56cf1df5bd20f63 completed May 9, 2026, 10:37 p.m.
Created at: April 10, 2026, 4:53 a.m.