Triple

T32422067
Position Surface form Disambiguated ID Type / Status
Subject Sagan Tosu E828484 entity
Predicate predecessor P97 FINISHED
Object Tosu Futures
Tosu Futures was a former Japanese professional football club based in Tosu, Saga Prefecture, that competed in the Japan Football League before being reorganized into what is now Sagan Tosu.
E2006335 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: Tosu Futures | Statement: [Sagan Tosu, predecessor, Tosu Futures]
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: Tosu Futures
Triple: [Sagan Tosu, predecessor, Tosu Futures]
Generated description
Tosu Futures was a former Japanese professional football club based in Tosu, Saga Prefecture, that competed in the Japan Football League before being reorganized into what is now Sagan Tosu.

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_69f3491b28bc8190b75cea7a507f337b completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c28269d08190a72a4ca90e219286 completed May 3, 2026, 3:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f26753881909bae5c3a867dce5a completed June 18, 2026, 8:03 p.m.
NEDg Description generation batch_6a3450be40708190a12bfb352cd508d0 completed June 18, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a345c04b9c88190b95ae85c88b42f17 completed June 18, 2026, 8:58 p.m.
Created at: May 1, 2026, 12:54 a.m.