Triple

T22271380
Position Surface form Disambiguated ID Type / Status
Subject Shiga Lakestars E550484 entity
Predicate fullName P16 FINISHED
Object Shiga Lakestars NE NERFINISHED

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: Shiga Lakestars | Statement: [Shiga Lakestars, fullName, Shiga Lakestars]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shiga Lakestars
Context triple: [Shiga Lakestars, fullName, Shiga Lakestars]
  • A. Shiga Lakestars chosen
    Shiga Lakestars is a professional basketball team based in Shiga Prefecture, Japan, competing in the country’s top-tier B.League.
  • B. Daimai Orions
    Daimai Orions was a former Japanese professional baseball team that later became known as the Chiba Lotte Marines.
  • C. Charlotte Stars
    The Charlotte Stars were a professional American football team that competed in the World Football League.
  • D. Niseko United
    Niseko United is a renowned ski resort area in Hokkaido, Japan, comprising several interconnected ski resorts known for abundant powder snow and extensive terrain.
  • E. Nagoya Fighting Eagles
    Nagoya Fighting Eagles is a professional Japanese basketball team based in Nagoya that competes in the B.League.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e43d8208190aff4f9cf7f2c2a8a completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f141c056cc819088dae6f2b9a1d526 completed April 28, 2026, 11:24 p.m.
Created at: April 16, 2026, 8:40 p.m.