Triple
T19598539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | César Azpilicueta |
E470407
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Azpi
Azpi is the widely used nickname of Spanish professional footballer César Azpilicueta, known for his long and successful spell as a versatile defender at Chelsea FC.
|
E1384924
|
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: Azpi | Statement: [César Azpilicueta, nickname, Azpi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azpi Context triple: [César Azpilicueta, nickname, Azpi]
-
A.
Azpeitia
Azpeitia is a town in the province of Gipuzkoa in Spain’s Basque Country, known as the birthplace of Saint Ignatius of Loyola.
-
B.
Aramburu
Aramburu is a Spanish-language surname of Basque origin borne by various notable figures in politics, religion, and sports.
-
C.
Aranzazu
Aranzazu is a small Colombian town located in the mountainous coffee-growing region of the Caldas Department.
-
D.
Asón
Asón is a river in northern Spain known for its scenic karst landscapes and waterfall-rich upper course in the region of Cantabria.
-
E.
Azkoitia
Azkoitia is a town in the province of Gipuzkoa in Spain’s Basque Country, known for its industrial history and location in the Urola valley.
- 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: Azpi Triple: [César Azpilicueta, nickname, Azpi]
Generated description
Azpi is the widely used nickname of Spanish professional footballer César Azpilicueta, known for his long and successful spell as a versatile defender at Chelsea FC.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Azpi Target entity description: Azpi is the widely used nickname of Spanish professional footballer César Azpilicueta, known for his long and successful spell as a versatile defender at Chelsea FC.
-
A.
Azpeitia
Azpeitia is a town in the province of Gipuzkoa in Spain’s Basque Country, known as the birthplace of Saint Ignatius of Loyola.
-
B.
Aramburu
Aramburu is a Spanish-language surname of Basque origin borne by various notable figures in politics, religion, and sports.
-
C.
Aranzazu
Aranzazu is a small Colombian town located in the mountainous coffee-growing region of the Caldas Department.
-
D.
Asón
Asón is a river in northern Spain known for its scenic karst landscapes and waterfall-rich upper course in the region of Cantabria.
-
E.
Azkoitia
Azkoitia is a town in the province of Gipuzkoa in Spain’s Basque Country, known for its industrial history and location in the Urola valley.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407c52c081908704d3a4dd6e853b |
completed | April 20, 2026, 3:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a075f1be2d48190a1beec726ea4e410 |
completed | May 15, 2026, 5:59 p.m. |
| NEDg | Description generation | batch_6a075fde0d8c8190aefc4a06beda2c79 |
completed | May 15, 2026, 6:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a076039f7188190add1c65a4a9e32ce |
completed | May 15, 2026, 6:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.