Triple

T26561358
Position Surface form Disambiguated ID Type / Status
Subject Corryong E666249 entity
Predicate roadConnection P385 FINISHED
Object Benambra–Corryong Road
Benambra–Corryong Road is a rural arterial route in southeastern Australia that links the Victorian high country around Benambra with the town of Corryong in northeastern Victoria.
E1819310 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: Benambra–Corryong Road | Statement: [Corryong, roadConnection, Benambra–Corryong 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: Benambra–Corryong Road
Triple: [Corryong, roadConnection, Benambra–Corryong Road]
Generated description
Benambra–Corryong Road is a rural arterial route in southeastern Australia that links the Victorian high country around Benambra with the town of Corryong in northeastern Victoria.

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_69ee9cf7e94481909f0d556b36e43572 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f6146c6e188190aa022ef2b9ee1774 completed May 2, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a164154ce1881908206b07bfcbfe378 completed May 27, 2026, 12:56 a.m.
NEDg Description generation batch_6a1642a04a9c81908f196894b8f4bdf5 completed May 27, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a164322f1148190b37794a5fc54f184 completed May 27, 2026, 1:04 a.m.
Created at: April 27, 2026, 1:52 a.m.