Triple

T8758103
Position Surface form Disambiguated ID Type / Status
Subject Pemon language E208122 entity
Predicate hasDialect P4251 FINISHED
Object Taurepán
Taurepán is a dialect of the Pemon language spoken by an Indigenous group in the Gran Sabana region of southeastern Venezuela.
 E755543 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: Taurepán | Statement: [Pemon language, hasDialect, Taurepán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taurepán
Context triple: [Pemon language, hasDialect, Taurepán]
  • A. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • B. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • C. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • D. Mora
    Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
  • E. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • 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: Taurepán
Triple: [Pemon language, hasDialect, Taurepán]
Generated description
Taurepán is a dialect of the Pemon language spoken by an Indigenous group in the Gran Sabana region of southeastern Venezuela.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taurepán
Target entity description: Taurepán is a dialect of the Pemon language spoken by an Indigenous group in the Gran Sabana region of southeastern Venezuela.
  • A. Mora
    Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
  • B. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • C. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • D. Mora
    Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
  • E. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • 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_69ca835cd6b08190bd7c63db92f53c86 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ddc2d9c81908948aee2b956cce4 completed March 31, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf434232d08190bfee6f5ec1c0b5a6 completed April 3, 2026, 4:34 a.m.
NEDg Description generation batch_69cf4569352c819089745287789d0b70 completed April 3, 2026, 4:43 a.m.
NED2 Entity disambiguation (via description) batch_69cf45d053248190b7f7a5e2646d31b4 completed April 3, 2026, 4:45 a.m.
Created at: March 30, 2026, 6:40 p.m.