Triple

T25215378
Position Surface form Disambiguated ID Type / Status
Subject Commonwealth Short Story Prize E631812 entity
Predicate hasCategory P87 FINISHED
Object Commonwealth literary awards
Commonwealth literary awards are a group of prestigious prizes recognizing outstanding fiction and other literary works by writers from countries in the Commonwealth of Nations.
E1671940 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: Commonwealth literary awards | Statement: [Commonwealth Short Story Prize, hasCategory, Commonwealth literary 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: Commonwealth literary awards
Triple: [Commonwealth Short Story Prize, hasCategory, Commonwealth literary awards]
Generated description
Commonwealth literary awards are a group of prestigious prizes recognizing outstanding fiction and other literary works by writers from countries in the Commonwealth of Nations.

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_69e75a8d1aa48190a4320acd3654762c completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47b8bd25c819089de15eac12cd285 completed May 1, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067d3f8f881909da835686315ca94 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1068d5ff248190b9efb77366147c26 completed May 22, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1069cb170c8190b31daf74fff26c35 completed May 22, 2026, 2:35 p.m.
Created at: April 21, 2026, 12:59 p.m.