Triple
T19279989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Antonio Galán |
E482161
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Galán
Galán is a Spanish surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
|
E1367230
|
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: Galán | Statement: [José Antonio Galán, familyName, Galán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Galán Context triple: [José Antonio Galán, familyName, Galán]
-
A.
Froilán
Froilán is a Spanish royal family member, the grandson of former King Juan Carlos I and nephew of King Felipe VI of Spain.
-
B.
Maragall
Maragall is a Barcelona Metro station that serves as an interchange point between multiple lines in the city’s public transit network.
-
C.
Blasco
Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
-
D.
Rollán
Rollán is the Spanish family name of actress Maribel Verdú, known for her prominent roles in Spanish and international cinema.
-
E.
Íñigo
Íñigo is the Basque given name of Ignatius of Loyola, the 16th-century Spanish priest who founded the Society of Jesus (Jesuits).
- 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: Galán Triple: [José Antonio Galán, familyName, Galán]
Generated description
Galán is a Spanish surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Galán Target entity description: Galán is a Spanish surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
-
A.
Froilán
Froilán is a Spanish royal family member, the grandson of former King Juan Carlos I and nephew of King Felipe VI of Spain.
-
B.
Maragall
Maragall is a Barcelona Metro station that serves as an interchange point between multiple lines in the city’s public transit network.
-
C.
Blasco
Blasco is a masculine given name of Spanish origin, historically borne by notable figures such as colonial administrators and writers.
-
D.
Rollán
Rollán is the Spanish family name of actress Maribel Verdú, known for her prominent roles in Spanish and international cinema.
-
E.
Íñigo
Íñigo is the Basque given name of Ignatius of Loyola, the 16th-century Spanish priest who founded the Society of Jesus (Jesuits).
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbfdfaf481909e0434f33053cc62 |
completed | April 20, 2026, 10:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e7ba04481908e8b707d34028e58 |
completed | May 15, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a070f74709481909b4eb1c073db2134 |
completed | May 15, 2026, 12:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070fccff7c819083fe388dda8e4e5a |
completed | May 15, 2026, 12:21 p.m. |
Created at: April 10, 2026, 1:30 p.m.