Triple

T14837267
Position Surface form Disambiguated ID Type / Status
Subject Molten basketball E348863 entity
Predicate hasModel P2390 FINISHED
Object Molten GL7 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 GL7 | Statement: [Molten basketball, hasModel, Molten GL7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molten GL7
Context triple: [Molten basketball, hasModel, Molten GL7]
  • 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. Meteor T.7
    The Meteor T.7 is a two-seat trainer version of the British Gloster Meteor jet fighter, used primarily for pilot instruction and conversion training.
  • D. SA-17 Grizzly
    SA-17 Grizzly is the NATO reporting name for a Russian-made, medium-range, mobile surface-to-air missile system designed to engage aircraft, cruise missiles, and other aerial threats.
  • E. Migrol
    Migrol is a Swiss energy and fuel company best known for operating a nationwide network of petrol stations and heating oil services as part of the Migros Group.
  • 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_69fe38a813b881908a71350073c8fc5c completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:52 a.m.