Triple

T27446947
Position Surface form Disambiguated ID Type / Status
Subject Nattai River E692308 entity
Predicate flowsNear P350 FINISHED
Object Buxton, New South Wales
Buxton, New South Wales is a small rural village in the Macarthur region of New South Wales, Australia, known for its bushland setting and proximity to national parks and nature reserves.
 E1773326 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: Buxton, New South Wales | Statement: [Nattai River, flowsNear, Buxton, New South Wales]
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: Buxton, New South Wales
Triple: [Nattai River, flowsNear, Buxton, New South Wales]
Generated description
Buxton, New South Wales is a small rural village in the Macarthur region of New South Wales, Australia, known for its bushland setting and proximity to national parks and nature reserves.

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_69ef5206c9248190b5975c2a7f9d229c completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d93317481908cffe1d3d1b8ad83 completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b25bd1388190836532150eaf8e05 completed May 24, 2026, 8:10 a.m.
NEDg Description generation batch_6a12b3bde3588190810d8d2dffbc6438 completed May 24, 2026, 8:15 a.m.
NED2 Entity disambiguation (via description) batch_6a12b44191688190899b55266e559ede completed May 24, 2026, 8:18 a.m.
Created at: April 27, 2026, 12:46 p.m.