Triple

T32873457
Position Surface form Disambiguated ID Type / Status
Subject Don Banks E840854 entity
Predicate placeOfBirth P1 FINISHED
Object South Melbourne, Victoria, Australia
South Melbourne, Victoria, Australia is an inner-city suburb of Melbourne known for its historic Victorian-era architecture, vibrant markets, and close proximity to the central business district.
E2026718 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: South Melbourne, Victoria, Australia | Statement: [Don Banks, placeOfBirth, South Melbourne, Victoria, Australia]
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: South Melbourne, Victoria, Australia
Triple: [Don Banks, placeOfBirth, South Melbourne, Victoria, Australia]
Generated description
South Melbourne, Victoria, Australia is an inner-city suburb of Melbourne known for its historic Victorian-era architecture, vibrant markets, and close proximity to the 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_69f349436ee88190b72ee12d0f3f508e completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cfe90a4c81909662075cd8a8c715 completed May 3, 2026, 4:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bd1909ac81908dfc7c4c217fa6b4 completed June 19, 2026, 3:52 a.m.
NEDg Description generation batch_6a34bdc35a24819088892cb8a675a225 completed June 19, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_6a34be6eb1808190a6bc47b8d79489ed completed June 19, 2026, 3:58 a.m.
Created at: May 1, 2026, 1:17 a.m.