Triple

T14837270
Position Surface form Disambiguated ID Type / Status
Subject Molten basketball E348863 entity
Predicate hasModel P2390 FINISHED
Object Molten GM7 E153428 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: Molten GM7 | Statement: [Molten basketball, hasModel, Molten GM7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molten GM7
Context triple: [Molten basketball, hasModel, Molten GM7]
  • A. Melter
    Melter is a Marvel Comics supervillain known primarily as an enemy of Iron Man and a recurring member of villainous teams.
  • B. Molten chosen
    Molten is a Japanese sports equipment manufacturer best known for producing high-quality balls used in major international competitions across football, basketball, and other sports.
  • C. Micronite
    Micronite is a brand of cigarette filter historically associated with Kent cigarettes, known for its controversial use of asbestos in early filter designs.
  • D. Thermon
    Thermon is an ancient Greek sanctuary site in Aetolia, best known as a major religious and political center dedicated to the worship of Apollo.
  • E. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28d0ddc8190a34e3e2d469ab762 completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64fc8cdc8190a142a2a3ef889e72 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:52 a.m.