Triple

T24764887
Position Surface form Disambiguated ID Type / Status
Subject Nittaku Home Flyers E619553 entity
Predicate alsoKnownAs P39 FINISHED
Object Nittaku Flyers
Nittaku Flyers is a Japanese professional basketball team that competes in the country’s domestic leagues.
E1657185 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: Nittaku Flyers | Statement: [Nittaku Home Flyers, alsoKnownAs, Nittaku Flyers]
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: Nittaku Flyers
Triple: [Nittaku Home Flyers, alsoKnownAs, Nittaku Flyers]
Generated description
Nittaku Flyers is a Japanese professional basketball team that competes in the country’s domestic leagues.

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_69e2fabbea94819092ed41348909622f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410a4591c81909f918efd84a1f6f6 completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a103300c9c0819095376c4ef4272557 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034cf890881908bd25523cdb83586 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 4:28 a.m.