Triple
T2363859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marija Pejčinović Burić |
E47335
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marija |
E108095
|
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: Marija | Statement: [Marija Pejčinović Burić, givenName, Marija]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marija Context triple: [Marija Pejčinović Burić, givenName, Marija]
-
A.
Marija
chosen
Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
-
B.
Klaudija
Klaudija is a feminine given name, commonly used in Slavic countries, that corresponds to the name Claudia.
-
C.
Renata
Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
-
D.
Katia
Katia is the Atlantic hurricane name that was introduced to replace the retired name Katrina following the devastating 2005 storm.
-
E.
Melanija
Melanija is the Slovene given name of Melania Trump, the former First Lady of the United States and wife of Donald Trump.
- 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc746e7048190a09a38401b367628 |
completed | March 7, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea896e0388190aabff2d70787dc43 |
completed | March 9, 2026, 11:01 a.m. |
Created at: March 4, 2026, 7:55 p.m.