Triple

T25923512
Position Surface form Disambiguated ID Type / Status
Subject Brankov most E653237 entity
Predicate locatedIn P40 FINISHED
Object New Belgrade municipality
New Belgrade municipality is a large urban municipality of Belgrade, Serbia, known for its modernist architecture, extensive residential blocks, and role as a major business and commercial hub of the city.
E1700122 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: New Belgrade municipality | Statement: [Brankov most, locatedIn, New Belgrade municipality]
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: New Belgrade municipality
Triple: [Brankov most, locatedIn, New Belgrade municipality]
Generated description
New Belgrade municipality is a large urban municipality of Belgrade, Serbia, known for its modernist architecture, extensive residential blocks, and role as a major business and commercial hub of the city.

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_69e7ab3eb9b881909c1390690551f868 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603eb73688190a260029e23d0731b completed May 2, 2026, 2:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecd3de4c8190b07da99c5e98390d completed May 22, 2026, 11:55 p.m.
NEDg Description generation batch_6a10ef215b448190853f97729867b5fb completed May 23, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a10efc6a0e48190a595a5025ad5c926 completed May 23, 2026, 12:07 a.m.
Created at: April 22, 2026, 8:35 a.m.