Triple
T7013433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinara |
E162639
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object |
Kijevo
Kijevo is a small village in Croatia situated near Mount Dinara in the country’s inland Dalmatian region.
|
E635656
|
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: Kijevo | Statement: [Dinara, nearbySettlement, Kijevo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kijevo Context triple: [Dinara, nearbySettlement, Kijevo]
-
A.
Kraljevo
Kraljevo is a city in central Serbia known as a regional administrative and cultural center, situated near several important medieval Serbian monasteries.
-
B.
Nikšić
Nikšić is one of the largest cities in Montenegro, known as an important industrial, cultural, and educational center of the country.
-
C.
Jagodina
Jagodina is a city in central Serbia known as a regional industrial and cultural center, featuring attractions such as a popular zoo, aqua park, and museums.
-
D.
Kragujevac
Kragujevac is a central Serbian city historically significant as an early capital and industrial and cultural hub of the country.
-
E.
Kruševac
Kruševac is a historic city in central Serbia founded in the 14th century by Prince Lazar, serving briefly as the capital of his medieval Serbian principality.
- 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: Kijevo Triple: [Dinara, nearbySettlement, Kijevo]
Generated description
Kijevo is a small village in Croatia situated near Mount Dinara in the country’s inland Dalmatian region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kijevo Target entity description: Kijevo is a small village in Croatia situated near Mount Dinara in the country’s inland Dalmatian region.
-
A.
Kraljevo
Kraljevo is a city in central Serbia known as a regional administrative and cultural center, situated near several important medieval Serbian monasteries.
-
B.
Nikšić
Nikšić is one of the largest cities in Montenegro, known as an important industrial, cultural, and educational center of the country.
-
C.
Jagodina
Jagodina is a city in central Serbia known as a regional industrial and cultural center, featuring attractions such as a popular zoo, aqua park, and museums.
-
D.
Kragujevac
Kragujevac is a central Serbian city historically significant as an early capital and industrial and cultural hub of the country.
-
E.
Kruševac
Kruševac is a historic city in central Serbia founded in the 14th century by Prince Lazar, serving briefly as the capital of his medieval Serbian principality.
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc59cbfc8190bba9ebd14143d43c |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a4ff6148190a7a453328507fd6b |
completed | March 28, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69c76c23b3f881909c4aa800690c0293 |
completed | March 28, 2026, 5:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76cb513d881909da349b4b4b88a61 |
completed | March 28, 2026, 5:52 a.m. |
Created at: March 27, 2026, 2:34 p.m.