Triple
T1655450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafael Garza Gutiérrez |
E35787
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Garza
Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
|
E192398
|
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: Garza | Statement: [Rafael Garza Gutiérrez, familyName, Garza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garza Context triple: [Rafael Garza Gutiérrez, familyName, Garza]
-
A.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
-
B.
Sosa
Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
-
C.
Herrera
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
-
D.
Magaña
Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
-
E.
Rafael Garza Gutiérrez
Rafael Garza Gutiérrez was a Mexican footballer and coach best known as a founding figure and early leader of Club América, one of Mexico’s most successful and popular soccer teams.
- 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: Garza Triple: [Rafael Garza Gutiérrez, familyName, Garza]
Generated description
Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Garza Target entity description: Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
-
A.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
-
B.
Sosa
Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
-
C.
Herrera
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
-
D.
Magaña
Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
-
E.
Rafael Garza Gutiérrez
Rafael Garza Gutiérrez was a Mexican footballer and coach best known as a founding figure and early leader of Club América, one of Mexico’s most successful and popular soccer teams.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a8b597c81908a62b41718d85df6 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8abe91bc8190ba363e1f7fd07b9f |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad9575acf88190aa3fe80794534dd4 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97a7128c819097ff36216f00d4f9 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:29 p.m.