Triple

T23440405
Position Surface form Disambiguated ID Type / Status
Subject R59 road E565381 entity
Predicate connectsCity P4245 FINISHED
Object Johannesburg (southern suburbs)
Johannesburg (southern suburbs) is a largely residential and industrial area of Johannesburg, South Africa, encompassing a mix of suburbs and townships south of the city’s central business district.
E1620162 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: Johannesburg (southern suburbs) | Statement: [R59 road, connectsCity, Johannesburg (southern suburbs)]
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: Johannesburg (southern suburbs)
Triple: [R59 road, connectsCity, Johannesburg (southern suburbs)]
Generated description
Johannesburg (southern suburbs) is a largely residential and industrial area of Johannesburg, South Africa, encompassing a mix of suburbs and townships south of the city’s central business district.

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_69e24584f9488190bb32730bd2ce023e completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5df28288190936f16b017a20bc0 completed April 29, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0face621208190853836605f5fb269 completed May 22, 2026, 1:09 a.m.
NEDg Description generation batch_6a0fadf24a1c8190bf530988ba1b86de completed May 22, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_6a0faeb55b6c8190944d1bd621b3f819 completed May 22, 2026, 1:17 a.m.
Created at: April 17, 2026, 5:50 p.m.