Triple

T25848368
Position Surface form Disambiguated ID Type / Status
Subject Ostružnica E651132 entity
Predicate partOf P40 FINISHED
Object Belgrade metropolitan area
The Belgrade metropolitan area is the densely populated urban region centered on Serbia's capital city, encompassing Belgrade and its surrounding suburbs, municipalities, and satellite settlements.
E444145 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: Belgrade metropolitan area | Statement: [Ostružnica, partOf, Belgrade metropolitan area]
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: Belgrade metropolitan area
Triple: [Ostružnica, partOf, Belgrade metropolitan area]
Generated description
The Belgrade metropolitan area is the densely populated urban region centered on Serbia's capital city, encompassing Belgrade and its surrounding suburbs, municipalities, and satellite settlements.

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_69e7ab39035c8190be15c8aaee1bb858 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f60239fb6881908503759ddd6b3fb1 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1303181c608190b38ce10b7f19f546 completed May 24, 2026, 1:54 p.m.
NEDg Description generation batch_6a1303b88b088190b5afdfb3995ab960 completed May 24, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a13044d6a8c8190b9904e442ba6fd2f completed May 24, 2026, 1:59 p.m.
Created at: April 22, 2026, 7:57 a.m.