Triple
T12334484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria of Portugal (infanta) |
E294048
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Maria
Maria of Portugal was a Portuguese infanta (princess) from the royal House of Aviz.
|
E979761
|
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: Maria | Statement: [Maria of Portugal (infanta), givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria of Portugal (infanta), givenName, Maria]
-
A.
Maria
Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
-
B.
Maria
Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
-
C.
Maria
Maria is a track on Rage Against the Machine’s 2000 album "The Battle of Los Angeles," known for its politically charged lyrics and aggressive rap metal sound.
-
D.
Maria
Maria I of Portugal was the first queen regnant of Portugal, known for her devout Catholicism, initial period of enlightened reforms, and later mental illness that led to her son acting as regent.
-
E.
Maria
Maria is a witty and sharp-tongued lady-in-waiting to the Princess of France in William Shakespeare’s comedy "Love's Labour's Lost."
- 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: Maria Triple: [Maria of Portugal (infanta), givenName, Maria]
Generated description
Maria of Portugal was a Portuguese infanta (princess) from the royal House of Aviz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Target entity description: Maria of Portugal was a Portuguese infanta (princess) from the royal House of Aviz.
-
A.
Maria
Maria of Spain was an Infanta of Spain, the daughter of King Philip II and his fourth wife Anna of Austria, known primarily for her role within the Habsburg dynastic network in late 16th-century Europe.
-
B.
Maria
Maria of Spain was a Spanish royal figure known primarily as a member of the House of Bourbon in the 18th century.
-
C.
Maria
Maria II of Portugal was a 19th-century queen who twice ruled Portugal and played a key role in the country’s transition from absolutism to constitutional monarchy.
-
D.
Maria
Maria I of Portugal was the first queen regnant of Portugal, known for her devout Catholicism, initial period of enlightened reforms, and later mental illness that led to her son acting as regent.
-
E.
Maria
Maria is the given name of Maria Christina of the Netherlands, a 19th-century Dutch princess and member of the House of Orange-Nassau.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f64ad20819080d99e57833b4b51 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a97614c8190b67e07df3e424e32 |
completed | May 2, 2026, 4:47 p.m. |
| NEDg | Description generation | batch_69f62be420308190bcb00d8b37b09ea2 |
completed | May 2, 2026, 4:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f63050f5d48190881688d12c4c1819 |
completed | May 2, 2026, 5:11 p.m. |
Created at: April 8, 2026, 9:53 p.m.