Triple

T20380288
Position Surface form Disambiguated ID Type / Status
Subject Orco E497806 entity
Predicate hasTributary P415 FINISHED
Object Malesina
Malesina is a town in Central Greece, known for its proximity to the Malian Gulf and its role in the local agricultural and coastal economy.
 E1426006 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: Malesina | Statement: [Orco, hasTributary, Malesina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Malesina
Context triple: [Orco, hasTributary, Malesina]
  • A. Guajibo
    Guajibo is an Indigenous people of the Llanos region of Colombia and Venezuela, known for their Guahiboan language and traditionally semi-nomadic, cattle-herding lifestyle.
  • B. Guática
    Guática is a small municipality and town in the Colombian department of Risaralda, known for its rural Andean landscapes and coffee-growing economy.
  • C. Mocama
    Mocama were a coastal Timucua-speaking Indigenous people who inhabited the northeastern Florida and southeastern Georgia shoreline at the time of European contact.
  • D. Tamanique
    Tamanique is a small town and municipality in western El Salvador known for its nearby waterfalls and coastal proximity.
  • E. Guana
    Guana is a dialect of the Terena language spoken by Indigenous communities in parts of South America.
  • 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: Malesina
Triple: [Orco, hasTributary, Malesina]
Generated description
Malesina is a town in Central Greece, known for its proximity to the Malian Gulf and its role in the local agricultural and coastal economy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Malesina
Target entity description: Malesina is a town in Central Greece, known for its proximity to the Malian Gulf and its role in the local agricultural and coastal economy.
  • A. Guajibo
    Guajibo is an Indigenous people of the Llanos region of Colombia and Venezuela, known for their Guahiboan language and traditionally semi-nomadic, cattle-herding lifestyle.
  • B. Guática
    Guática is a small municipality and town in the Colombian department of Risaralda, known for its rural Andean landscapes and coffee-growing economy.
  • C. Mocama
    Mocama were a coastal Timucua-speaking Indigenous people who inhabited the northeastern Florida and southeastern Georgia shoreline at the time of European contact.
  • D. Tamanique
    Tamanique is a small town and municipality in western El Salvador known for its nearby waterfalls and coastal proximity.
  • E. Guana
    Guana is a dialect of the Terena language spoken by Indigenous communities in parts of South America.
  • 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_69e0b4a5b7908190a972e4e7e698ae94 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e678b026e081909541e545886c8380 completed April 20, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a087095286c8190afdcb855220526fc completed May 16, 2026, 1:26 p.m.
NEDg Description generation batch_6a08712a87c081909c719be069819f03 completed May 16, 2026, 1:29 p.m.
NED2 Entity disambiguation (via description) batch_6a08719a13048190b0bb8c8a38bad7a9 completed May 16, 2026, 1:31 p.m.
Created at: April 16, 2026, 11:27 a.m.