Triple

T34730328
Position Surface form Disambiguated ID Type / Status
Subject Brisbane Northside E1001189 entity
Predicate hasTransportInfrastructure P2560 FINISHED
Object Gympie Road
Gympie Road is a major arterial route on Brisbane’s northside that serves as a key corridor for commuter and commercial traffic.
E2110448 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: Gympie Road | Statement: [Brisbane Northside, hasTransportInfrastructure, Gympie Road]
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: Gympie Road
Triple: [Brisbane Northside, hasTransportInfrastructure, Gympie Road]
Generated description
Gympie Road is a major arterial route on Brisbane’s northside that serves as a key corridor for commuter and commercial traffic.

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_69f76daeb6e48190a4c9a6b0edc80f72 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779abc3048190bc1f5e57c494d959 completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a375bedf74c8190aba79056e2d3f149 completed June 21, 2026, 3:35 a.m.
NEDg Description generation batch_6a375d09dfbc81909eddba9593dafbb2 completed June 21, 2026, 3:39 a.m.
NED2 Entity disambiguation (via description) batch_6a3760f4f2c88190998d890243e41710 completed June 21, 2026, 3:56 a.m.
Created at: May 3, 2026, 3:59 p.m.