Triple
T21236764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria of Portugal |
E523364
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maria |
—
|
NE NERFINISHED |
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: Maria | Statement: [Maria of Portugal, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria of Portugal, givenName, Maria]
-
A.
Maria
Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
-
B.
Maria
Maria is a coastal municipality on Siquijor Island in the Philippines known for its rural communities and scenic seaside landscapes.
-
C.
Maria
Maria Vladimirovna Dolgorukova was a Russian noblewoman from the prominent Dolgorukov family, known historically as the first wife of Tsar Michael I of Russia.
-
D.
Maria
Maria is the given name of Grand Duchess Maria Alexandrovna of Russia, a 19th-century Russian imperial princess who became Duchess of Edinburgh through marriage into the British royal family.
-
E.
Maria
Maria is the given name of Maria Ludovika of Austria-Este, an Empress consort of Austria in the early 19th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735202c7481909c642ddaafb40671 |
completed | April 21, 2026, 8:28 a.m. |
Created at: April 16, 2026, 3:46 p.m.