Triple
T4041671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Croatia |
E83964
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Zagreb |
E31635
|
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: Zagreb | Statement: [Kingdom of Croatia, hasCapital, Zagreb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zagreb Context triple: [Kingdom of Croatia, hasCapital, Zagreb]
-
A.
Zagreb
chosen
Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
-
B.
Osijek
Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
-
C.
Sarajevo
Sarajevo is the capital and largest city of Bosnia and Herzegovina, historically known as the site of Archduke Franz Ferdinand’s assassination that sparked World War I.
-
D.
Rijeka
Rijeka is a significant Croatian port city on the Adriatic Sea, known for its maritime industry, cultural heritage, and role as a key transport hub.
-
E.
Barajevo
Barajevo is a suburban municipality of Belgrade, Serbia, located in the southern part of the city’s administrative area.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb3a9314819095dcf47675eedb48 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b4d2cb081908dbca3bee5610cda |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:37 p.m.