Triple

T27129920
Position Surface form Disambiguated ID Type / Status
Subject AAGPS Athletics Championships E681535 entity
Predicate memberSchoolsCompete P87172 FINISHED
Object The King’s School
The King’s School is a prestigious independent Anglican day and boarding school for boys in Parramatta, Sydney, renowned for its strong academic and sporting traditions.
E1761068 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: The King’s School | Statement: [AAGPS Athletics Championships, memberSchoolsCompete, The King’s School]
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: The King’s School
Triple: [AAGPS Athletics Championships, memberSchoolsCompete, The King’s School]
Generated description
The King’s School is a prestigious independent Anglican day and boarding school for boys in Parramatta, Sydney, renowned for its strong academic and sporting traditions.

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_69eefacbcc2081909ebf00daa23f1981 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6d272f31c819082d519f2cb96d8cc completed May 3, 2026, 4:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a125378b4888190b3cd17f1964926c2 completed May 24, 2026, 1:25 a.m.
NEDg Description generation batch_6a12546f814881908c806a1805b7473d completed May 24, 2026, 1:29 a.m.
NED2 Entity disambiguation (via description) batch_6a12552837d88190a12496ca49423f0f completed May 24, 2026, 1:32 a.m.
Created at: April 27, 2026, 9:03 a.m.