Triple

T35588654
Position Surface form Disambiguated ID Type / Status
Subject Hilton, South Australia E1028430 entity
Predicate nearbySuburb P41355 FINISHED
Object Richmond, South Australia
Richmond, South Australia is an inner-western suburb of Adelaide known for its residential character, proximity to the city centre, and access to major transport routes.
E2152531 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: Richmond, South Australia | Statement: [Hilton, South Australia, nearbySuburb, Richmond, South 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: Richmond, South Australia
Triple: [Hilton, South Australia, nearbySuburb, Richmond, South Australia]
Generated description
Richmond, South Australia is an inner-western suburb of Adelaide known for its residential character, proximity to the city centre, and access to major transport routes.

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_69f76e0495a081909beced418558c0b4 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79e898af88190a6da2631e291230f completed May 3, 2026, 7:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387cfd98b08190b124837f0ab538fc completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387da3cca88190871b690e2ee62c9e completed June 22, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a387e3b94cc8190bfc6b69d756793fb completed June 22, 2026, 12:13 a.m.
Created at: May 3, 2026, 4:05 p.m.