Triple
T1000551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diego Velázquez de Cuéllar |
E21592
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
de Cuéllar
de Cuéllar is a Spanish surname historically associated with figures such as the conquistador Diego Velázquez de Cuéllar.
|
E128067
|
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: de Cuéllar | Statement: [Diego Velázquez de Cuéllar, familyName, de Cuéllar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de Cuéllar Context triple: [Diego Velázquez de Cuéllar, familyName, de Cuéllar]
-
A.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
B.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
-
C.
Durán
Durán is an Ecuadorian city in the Guayas Province, located across the Guayas River from Guayaquil and serving as an important transport and industrial hub.
-
D.
San Borja
San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
-
E.
de León
De León is a Spanish surname of Sephardic Jewish origin historically associated with notable figures in religious and cultural scholarship.
- 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: de Cuéllar Triple: [Diego Velázquez de Cuéllar, familyName, de Cuéllar]
Generated description
de Cuéllar is a Spanish surname historically associated with figures such as the conquistador Diego Velázquez de Cuéllar.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: de Cuéllar Target entity description: de Cuéllar is a Spanish surname historically associated with figures such as the conquistador Diego Velázquez de Cuéllar.
-
A.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
B.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
-
C.
Durán
Durán is an Ecuadorian city in the Guayas Province, located across the Guayas River from Guayaquil and serving as an important transport and industrial hub.
-
D.
San Borja
San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
-
E.
de León
De León is a Spanish surname of Sephardic Jewish origin historically associated with notable figures in religious and cultural scholarship.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac537d788c81908d239f102626bdd6 |
completed | March 7, 2026, 4:34 p.m. |
| NEDg | Description generation | batch_69ac544fc41881908daff6b313622619 |
completed | March 7, 2026, 4:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5526679081909c9f7458bd316ff6 |
completed | March 7, 2026, 4:41 p.m. |
Created at: March 1, 2026, 7:41 p.m.