Triple

T36970234
Position Surface form Disambiguated ID Type / Status
Subject Dutch ship Leeuwin E914543 entity
Predicate influencedToponym P20713 FINISHED
Object Leeuwin region
The Leeuwin region is a coastal area in Western Australia named after the Dutch ship Leeuwin, known for its rugged shoreline, rich marine life, and prominent wine-producing districts.
E2211636 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: Leeuwin region | Statement: [Dutch ship Leeuwin, influencedToponym, Leeuwin region]
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: Leeuwin region
Triple: [Dutch ship Leeuwin, influencedToponym, Leeuwin region]
Generated description
The Leeuwin region is a coastal area in Western Australia named after the Dutch ship Leeuwin, known for its rugged shoreline, rich marine life, and prominent wine-producing districts.

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_69f76e8d13b4819089af24a47ce092fc completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9ff46ae648190aaf4f1a3406d5727 completed May 5, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c2995ec81909ab897c1bbc03c2f completed June 26, 2026, 2:26 p.m.
NEDg Description generation batch_6a3e9857472481909be66aa78d837027 completed June 26, 2026, 3:18 p.m.
NED2 Entity disambiguation (via description) batch_6a3eef76bbac81908dc5b35369a93018 completed June 26, 2026, 9:30 p.m.
Created at: May 3, 2026, 4:14 p.m.