Triple
T8987557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlético Nacional |
E214706
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Verdolagas
Verdolagas is the popular nickname of Atlético Nacional, one of Colombia’s most successful and widely supported football clubs.
|
E533202
|
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: Verdolagas | Statement: [Atlético Nacional, nickname, Verdolagas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verdolagas Context triple: [Atlético Nacional, nickname, Verdolagas]
-
A.
Verdolagas
Verdolagas is the popular nickname of Honduran football club Marathón, one of the country’s most traditional and successful teams.
-
B.
Naranjal
Naranjal is a town and canton in southwestern Ecuador known for its agricultural production and location within Guayas Province.
-
C.
Patachou
Patachou was a celebrated French singer, actress, and Parisian cabaret owner known for her warm voice and interpretations of classic chanson.
-
D.
Yerbas Buenas
Yerbas Buenas is a historic rural town and municipality in Chile’s Maule Region, known for its colonial heritage and role in the country’s independence era.
-
E.
Sarraméa
Sarraméa is a small inland commune in New Caledonia known for its lush mountainous landscapes and eco-tourism activities.
- 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: Verdolagas Triple: [Atlético Nacional, nickname, Verdolagas]
Generated description
Verdolagas is the popular nickname of Atlético Nacional, one of Colombia’s most successful and widely supported football clubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verdolagas Target entity description: Verdolagas is the popular nickname of Atlético Nacional, one of Colombia’s most successful and widely supported football clubs.
-
A.
Verdolagas
chosen
Verdolagas is the popular nickname of Honduran football club Marathón, one of the country’s most traditional and successful teams.
-
B.
Naranjal
Naranjal is a town and canton in southwestern Ecuador known for its agricultural production and location within Guayas Province.
-
C.
Patachou
Patachou was a celebrated French singer, actress, and Parisian cabaret owner known for her warm voice and interpretations of classic chanson.
-
D.
Yerbas Buenas
Yerbas Buenas is a historic rural town and municipality in Chile’s Maule Region, known for its colonial heritage and role in the country’s independence era.
-
E.
Sarraméa
Sarraméa is a small inland commune in New Caledonia known for its lush mountainous landscapes and eco-tourism activities.
- F. None of above.
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_69ca839f76bc8190a4b7123cdd682199 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67ef19108190ac518c4f744b6d60 |
completed | April 1, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0c155cc819087f1060454da38e5 |
completed | April 3, 2026, 2:37 p.m. |
| NEDg | Description generation | batch_69cfd15c82208190adc11bc6ab1b959b |
completed | April 3, 2026, 2:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfd1eb7f588190a7b7a4ccb48a51d9 |
completed | April 3, 2026, 2:42 p.m. |
Created at: March 30, 2026, 7:04 p.m.