Triple

T37935148
Position Surface form Disambiguated ID Type / Status
Subject Mitchell Freeway E946324 entity
Predicate hasInterchangeWith P1018 FINISHED
Object Burns Beach Road
Burns Beach Road is a major arterial road in Perth’s northern suburbs that connects coastal residential areas to the regional road network and the Mitchell Freeway.
E2250551 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: Burns Beach Road | Statement: [Mitchell Freeway, hasInterchangeWith, Burns Beach 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: Burns Beach Road
Triple: [Mitchell Freeway, hasInterchangeWith, Burns Beach Road]
Generated description
Burns Beach Road is a major arterial road in Perth’s northern suburbs that connects coastal residential areas to the regional road network and the Mitchell Freeway.

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_69f76ef531ac8190ae6d99e5786e76ec completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd9b50c88190b65d964e57e73530 completed May 6, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117f159008190a07ccc46cc3a3f15 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a41249f34188190a10752c13b25eb88 completed June 28, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_6a4125849a0c81909dfb528b35a55b60 completed June 28, 2026, 1:45 p.m.
Created at: May 3, 2026, 4:20 p.m.