Triple

T23794850
Position Surface form Disambiguated ID Type / Status
Subject Rakovica industrial area E588506 entity
Predicate belongsTo P35 FINISHED
Object Belgrade economic region
The Belgrade economic region is a major Serbian economic hub centered on the capital city, encompassing key industrial zones, commercial centers, and service sectors that drive much of the country’s economic activity.
 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 economic region | Statement: [Rakovica industrial area, belongsTo, Belgrade economic region]
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 economic region
Triple: [Rakovica industrial area, belongsTo, Belgrade economic region]
Generated description
The Belgrade economic region is a major Serbian economic hub centered on the capital city, encompassing key industrial zones, commercial centers, and service sectors that drive much of the country’s economic activity.

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_69e25d15db58819092ac1e6791696fd9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c6db34588190b05a44d1333fe177 completed April 29, 2026, 8:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1247c94bc48190af7b969991842c60 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a12488822208190aab1355ac3efd2a6 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124935c01c8190b9d6d13c4f50a104 completed May 24, 2026, 12:41 a.m.
Created at: April 17, 2026, 7:44 p.m.