Triple
T3327375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariana of Austria |
E69947
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mariana |
unclear NED1
|
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: Mariana | Statement: [Mariana of Austria, givenName, Mariana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mariana Context triple: [Mariana of Austria, givenName, Mariana]
-
A.
Mariana
"Mariana" is a famous 1851 Pre-Raphaelite painting by John Everett Millais depicting a solitary woman in a richly detailed interior, inspired by Shakespeare’s "Measure for Measure" and Tennyson’s poem of the same name.
-
B.
Mariana
Mariana is a neighborhood (barrio) within the city of Dorado, Puerto Rico.
-
C.
Catalina
Catalina is a feminine given name used in various Romance-language cultures, often considered a form of Catherine.
-
D.
Marín
Marín is a coastal town in the province of Pontevedra, Galicia, Spain, known for its naval traditions and as a base of the Spanish Navy.
-
E.
Culebrita
Culebrita is a small, uninhabited cay off the coast of Culebra, Puerto Rico, known for its pristine beaches, clear waters, and historic lighthouse.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb16f61248190bab10f4ac9e066f7 |
completed | March 8, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a7ce34c81908df0c30a41fd925c |
completed | March 12, 2026, 7:56 p.m. |
Created at: March 8, 2026, 3:12 p.m.