Triple

T25879413
Position Surface form Disambiguated ID Type / Status
Subject Toby Nankervis E652004 entity
Predicate originalTeam P76560 FINISHED
Object North Launceston Football Club
North Launceston Football Club is a historic Australian rules football club based in Launceston, Tasmania, known as one of the state’s most successful and prominent teams.
E1702201 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: North Launceston Football Club | Statement: [Toby Nankervis, originalTeam, North Launceston 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: North Launceston Football Club
Triple: [Toby Nankervis, originalTeam, North Launceston Football Club]
Generated description
North Launceston Football Club is a historic Australian rules football club based in Launceston, Tasmania, known as one of the state’s most successful and prominent teams.

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_69e7ab3ad9d88190841ddcb93ab02e96 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6033d54948190a52da9e6bef00afa completed May 2, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecb414b081908d486ba57890a65b completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10eddf8e008190a604d8c0db0fdd9d completed May 22, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a10efe2fc188190ab9d5e8276a1ef2f completed May 23, 2026, 12:08 a.m.
Created at: April 22, 2026, 8:13 a.m.