Triple

T33686092
Position Surface form Disambiguated ID Type / Status
Subject Werribee River E863034 entity
Predicate hasTributary P415 FINISHED
Object Lerderderg River
Lerderderg River is a waterway in central Victoria, Australia, known for its rugged gorge landscapes and role in regional recreation and conservation.
E2066102 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: Lerderderg River | Statement: [Werribee River, hasTributary, Lerderderg River]
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: Lerderderg River
Triple: [Werribee River, hasTributary, Lerderderg River]
Generated description
Lerderderg River is a waterway in central Victoria, Australia, known for its rugged gorge landscapes and role in regional recreation and conservation.

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_69f3498662b48190904442c39df84fb7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa64e3b881908b7995d1e4a0ee89 completed May 3, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c70763881909693772a92502c63 completed June 20, 2026, 9:25 a.m.
NEDg Description generation batch_6a365d2c51808190aa3437c2aa4af4d0 completed June 20, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a365de322208190b3fc9539d7a2b18b completed June 20, 2026, 9:31 a.m.
Created at: May 1, 2026, 1:43 a.m.