Triple

T30706093
Position Surface form Disambiguated ID Type / Status
Subject Keith Greig E781755 entity
Predicate originalTeam P76560 FINISHED
Object Brunswick Football Club
Brunswick Football Club was an Australian rules football club based in Melbourne that competed in the Victorian Football Association and produced several notable players.
E1928109 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: Brunswick Football Club | Statement: [Keith Greig, originalTeam, Brunswick Football Club]
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: Brunswick Football Club
Triple: [Keith Greig, originalTeam, Brunswick Football Club]
Generated description
Brunswick Football Club was an Australian rules football club based in Melbourne that competed in the Victorian Football Association and produced several notable players.

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_69f224abfcf081909492e64d3cc35262 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c19e9688190907e555dc9973ba0 completed May 2, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2898fd2fdc819094fb5f7cad6a1cab completed June 9, 2026, 10:51 p.m.
NEDg Description generation batch_6a2899a5f87881909200941832511700 completed June 9, 2026, 10:54 p.m.
NED2 Entity disambiguation (via description) batch_6a289ac7f570819094b7940133c5ac52 completed June 9, 2026, 10:59 p.m.
Created at: April 29, 2026, 8:35 p.m.