Triple
T5219402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loyola |
E117832
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Loyola y Oñaz |
E504048
|
NE FINISHED |
How this triple was built (2 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: Loyola y Oñaz | Statement: [Loyola, hasVariantSpelling, Loyola y Oñaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loyola y Oñaz Context triple: [Loyola, hasVariantSpelling, Loyola y Oñaz]
-
A.
Loyola de Oñaz
chosen
Loyola de Oñaz is the Basque noble family estate in Azpeitia, Spain, best known as the ancestral home and birthplace of Saint Ignatius of Loyola, founder of the Jesuits.
-
B.
Aramburu
Aramburu is a Spanish-language surname of Basque origin borne by various notable figures in politics, religion, and sports.
-
C.
Sorolla y Bastida
Sorolla y Bastida was a renowned Spanish painter of the late 19th and early 20th centuries, celebrated for his luminous, sun-drenched scenes and masterful use of light.
-
D.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
-
E.
Norzagaray
Norzagaray is a landlocked municipality in the province of Bulacan in the Philippines, known for its quarrying industry and natural attractions such as dams, rivers, and limestone formations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ab6e63c8190964b2b65a0206134 |
completed | March 20, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef8059c808190aac709a199541ce7 |
completed | March 21, 2026, 7:56 p.m. |
Created at: March 20, 2026, 1:48 p.m.