Triple

T34387131
Position Surface form Disambiguated ID Type / Status
Subject Forster, New South Wales E882583 entity
Predicate hasFeature P182 FINISHED
Object Wallis Lake estuary
Wallis Lake estuary is a large coastal waterway on the Mid North Coast of New South Wales, Australia, known for its clear waters, oyster farming, and recreational boating and fishing.
E2095956 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: Wallis Lake estuary | Statement: [Forster, New South Wales, hasFeature, Wallis Lake estuary]
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: Wallis Lake estuary
Triple: [Forster, New South Wales, hasFeature, Wallis Lake estuary]
Generated description
Wallis Lake estuary is a large coastal waterway on the Mid North Coast of New South Wales, Australia, known for its clear waters, oyster farming, and recreational boating and fishing.

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_69f349c0219881909393bbbc1edc8161 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f718783ba481908caedddcb144633e completed May 3, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370dbc940c8190b21c6b3aa7e136bd completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e7dcd88819091a402e550189e46 completed June 20, 2026, 10:04 p.m.
NED2 Entity disambiguation (via description) batch_6a370f2dba508190af182d53a385b955 completed June 20, 2026, 10:07 p.m.
Created at: May 1, 2026, 1:59 a.m.