Triple
T885033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croatia |
E19110
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object |
Osijek
Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
|
E133925
|
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: Osijek | Statement: [Croatia, majorCity, Osijek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osijek Context triple: [Croatia, majorCity, Osijek]
-
A.
Zagreb
Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
-
B.
Zrenjanin
Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat 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.
Novi Sad
Novi Sad is Serbia’s second-largest city and the cultural and economic center of the northern Vojvodina region, known for its historic architecture and the EXIT music festival.
- 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: Osijek Triple: [Croatia, majorCity, Osijek]
Generated description
Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Osijek Target entity description: Osijek is a prominent city in eastern Croatia known as an economic, cultural, and educational center of the Slavonia region.
-
A.
Zagreb
Zagreb is the capital and largest city of Croatia, known as a political, cultural, and economic hub in the Balkans.
-
B.
Zrenjanin
Zrenjanin is a city in northern Serbia known as an economic, cultural, and administrative center of the Banat 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.
Novi Sad
Novi Sad is Serbia’s second-largest city and the cultural and economic center of the northern Vojvodina region, known for its historic architecture and the EXIT music festival.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ace5e15c81908cc2e648c9cd52f2 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac660a86d881908ae96a5492c9b9a2 |
completed | March 7, 2026, 5:53 p.m. |
| NEDg | Description generation | batch_69ac67e76c3881908643b5b861826610 |
completed | March 7, 2026, 6:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac684ea69c819098beb37929bdb47a |
completed | March 7, 2026, 6:02 p.m. |
Created at: March 1, 2026, 7:39 p.m.