Triple

T34180528
Position Surface form Disambiguated ID Type / Status
Subject Budapest 9th District E876800 entity
Predicate borders P224 FINISHED
Object Budapest 21st District
Budapest 21st District, also known as Csepel, is a southern district of Budapest located on Csepel Island, characterized by its mix of industrial areas, residential neighborhoods, and Danube riverfront.
E2145256 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: Budapest 21st District | Statement: [Budapest 9th District, borders, Budapest 21st District]
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: Budapest 21st District
Triple: [Budapest 9th District, borders, Budapest 21st District]
Generated description
Budapest 21st District, also known as Csepel, is a southern district of Budapest located on Csepel Island, characterized by its mix of industrial areas, residential neighborhoods, and Danube riverfront.

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_69f349ae640c8190b9cd220b5368d8b6 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7100548bc8190b641d53a39abee5e completed May 3, 2026, 9:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3852cbf92881909d6e3ba5e0881e63 completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a38537cefd48190b5d223a5506b4f2d completed June 21, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a38546765988190bba6f0bc046274df completed June 21, 2026, 9:15 p.m.
Created at: May 1, 2026, 1:54 a.m.