Triple

T8232843
Position Surface form Disambiguated ID Type / Status
Subject Rif Republic E192332 entity
Predicate currency P245 FINISHED
Object Rifian peseta
The Rifian peseta was the official monetary unit used by the short-lived Rif Republic in northern Morocco during the early 20th century.
 E720657 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: Rifian peseta | Statement: [Rif Republic, currency, Rifian peseta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rifian peseta
Context triple: [Rif Republic, currency, Rifian peseta]
  • A. La Peseta
    La Peseta is a Madrid Metro station on Line 11 serving the La Peseta neighborhood in the Carabanchel district of Madrid, Spain.
  • B. Orlandi Valuta
    Orlandi Valuta is a money transfer and financial services brand owned by Western Union, primarily serving customers in the United States and Latin America.
  • C. Raha
    Raha is a town in the Nagaon district of Assam, India, known as the birthplace of prominent Indian freedom fighter and politician Gopinath Bordoloi.
  • D. Raha
    Raha is a coastal town and administrative center located on Muna Island in Southeast Sulawesi, Indonesia.
  • E. Pesa
    Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
  • 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: Rifian peseta
Triple: [Rif Republic, currency, Rifian peseta]
Generated description
The Rifian peseta was the official monetary unit used by the short-lived Rif Republic in northern Morocco during the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rifian peseta
Target entity description: The Rifian peseta was the official monetary unit used by the short-lived Rif Republic in northern Morocco during the early 20th century.
  • A. La Peseta
    La Peseta is a Madrid Metro station on Line 11 serving the La Peseta neighborhood in the Carabanchel district of Madrid, Spain.
  • B. Orlandi Valuta
    Orlandi Valuta is a money transfer and financial services brand owned by Western Union, primarily serving customers in the United States and Latin America.
  • C. Raha
    Raha is a coastal town and administrative center located on Muna Island in Southeast Sulawesi, Indonesia.
  • D. Raha
    Raha is a town in the Nagaon district of Assam, India, known as the birthplace of prominent Indian freedom fighter and politician Gopinath Bordoloi.
  • E. Pesa
    Pesa is a Polish manufacturer of rail vehicles, particularly known for producing modern trams and trains used in various European cities.
  • 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_69ca82db5b90819085d1ad7c2e27bfcc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb782658fc8190885dc267355ff245 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34e77fd08190a76f81de96d4e605 completed April 1, 2026, 3:08 p.m.
NEDg Description generation batch_69cd37a290508190b598f96220056041 completed April 1, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_69cd4eb519608190b5d0f534170214b5 completed April 1, 2026, 4:58 p.m.
Created at: March 30, 2026, 5:46 p.m.