Triple

T2741858
Position Surface form Disambiguated ID Type / Status
Subject Palo Monte E60767 entity
Predicate hasClericalRole P3092 FINISHED
Object tata nganga
Tata nganga is a high-ranking priest and ritual specialist in the Afro-Cuban Palo Monte religion, responsible for leading ceremonies, divination, and work with spiritual forces.
E295980 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: tata nganga | Statement: [Palo Monte, hasClericalRole, tata nganga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: tata nganga
Context triple: [Palo Monte, hasClericalRole, tata nganga]
  • A. Bobangi
    Bobangi is a Bantu language historically spoken along the Congo River that served as a major regional trade lingua franca in Central Africa.
  • B. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • C. Angangueo
    Angangueo is a historic mining town in central Mexico best known as a gateway to the Monarch Butterfly Biosphere Reserve.
  • D. Tangale
    Tangale is a West Chadic language spoken primarily in Gombe State, northeastern Nigeria, by the Tangale people.
  • E. Naku Tanti
    Naku Tanti is a celebrated literary work by the renowned Kannada poet D. R. Bendre, recognized as one of his most important contributions to modern Kannada poetry.
  • 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: tata nganga
Triple: [Palo Monte, hasClericalRole, tata nganga]
Generated description
Tata nganga is a high-ranking priest and ritual specialist in the Afro-Cuban Palo Monte religion, responsible for leading ceremonies, divination, and work with spiritual forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: tata nganga
Target entity description: Tata nganga is a high-ranking priest and ritual specialist in the Afro-Cuban Palo Monte religion, responsible for leading ceremonies, divination, and work with spiritual forces.
  • A. Bobangi
    Bobangi is a Bantu language historically spoken along the Congo River that served as a major regional trade lingua franca in Central Africa.
  • B. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • C. Angangueo
    Angangueo is a historic mining town in central Mexico best known as a gateway to the Monarch Butterfly Biosphere Reserve.
  • D. Tangale
    Tangale is a West Chadic language spoken primarily in Gombe State, northeastern Nigeria, by the Tangale people.
  • E. Naku Tanti
    Naku Tanti is a celebrated literary work by the renowned Kannada poet D. R. Bendre, recognized as one of his most important contributions to modern Kannada poetry.
  • 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb303898819098a7d192e29817f8 completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbca8ac081909ce86d4cd911b4f1 completed March 10, 2026, 6:35 a.m.
NEDg Description generation batch_69afbcc1dd988190826ab05e55adf1ee completed March 10, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69afbd452e1c8190a3ee9eaf642e80a0 completed March 10, 2026, 6:42 a.m.
Created at: March 6, 2026, 9:56 p.m.