Triple
T2231649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegon |
E48778
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Aegon Spain
Aegon Spain is the Spanish branch of the international insurance and financial services group Aegon, offering life insurance, pensions, and investment products in the Spanish market.
|
E245533
|
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: Aegon Spain | Statement: [Aegon, hasSubsidiary, Aegon Spain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aegon Spain Context triple: [Aegon, hasSubsidiary, Aegon Spain]
-
A.
Baltasar
Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
-
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.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
D.
Hernád
The Hernád is a river in Central Europe that flows through eastern Slovakia and northeastern Hungary before joining the Tisza River.
-
E.
Alfonso
Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
- 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: Aegon Spain Triple: [Aegon, hasSubsidiary, Aegon Spain]
Generated description
Aegon Spain is the Spanish branch of the international insurance and financial services group Aegon, offering life insurance, pensions, and investment products in the Spanish market.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aegon Spain Target entity description: Aegon Spain is the Spanish branch of the international insurance and financial services group Aegon, offering life insurance, pensions, and investment products in the Spanish market.
-
A.
Baltasar
Baltasar is a variant of the name Belshazzar, historically associated with the last king of Babylon mentioned in the biblical Book of Daniel.
-
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.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
D.
Hernád
The Hernád is a river in Central Europe that flows through eastern Slovakia and northeastern Hungary before joining the Tisza River.
-
E.
Alfonso
Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc06b7374819089fe643e12797bfd |
completed | March 7, 2026, 6:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae656a1f788190a08c3283bfedb6f4 |
completed | March 9, 2026, 6:15 a.m. |
| NEDg | Description generation | batch_69ae65d4f26481909808c97b95ca9b30 |
completed | March 9, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6670b6d88190a09023fae63f4000 |
completed | March 9, 2026, 6:19 a.m. |
Created at: March 4, 2026, 7:47 p.m.