Triple

T32438947
Position Surface form Disambiguated ID Type / Status
Subject World Rugby Sevens Player of the Year E828958 entity
Predicate organizer P123 FINISHED
Object World Rugby Awards
The World Rugby Awards are an annual ceremony organized by World Rugby to honor outstanding achievements and performances in international rugby across multiple categories.
E2014093 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: World Rugby Awards | Statement: [World Rugby Sevens Player of the Year, organizer, World Rugby Awards]
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: World Rugby Awards
Triple: [World Rugby Sevens Player of the Year, organizer, World Rugby Awards]
Generated description
The World Rugby Awards are an annual ceremony organized by World Rugby to honor outstanding achievements and performances in international rugby across multiple categories.

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_69f3491bf298819097b610f772d54a6d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e1a834819094e117bf9b6b3c15 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3485f6192c819090e1e4c110c36b6e completed June 18, 2026, 11:57 p.m.
NEDg Description generation batch_6a3486911d8c8190983388d7191b4d77 completed June 19, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a3487efeb248190b0d48dc5266c3927 completed June 19, 2026, 12:06 a.m.
Created at: May 1, 2026, 12:55 a.m.