Triple

T19408762
Position Surface form Disambiguated ID Type / Status
Subject Galazzano E485532 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object RSM 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: RSM | Statement: [Galazzano, vehicleRegistrationCode, RSM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RSM
Context triple: [Galazzano, vehicleRegistrationCode, RSM]
  • A. RSM chosen
    RSM is the international vehicle registration code used on license plates for vehicles registered in San Marino.
  • B. RSM
    RSM is the acronym for the NATO-led Resolute Support Mission in Afghanistan, focused on training, advising, and assisting Afghan security forces after the end of NATO’s combat operations.
  • C. RSM
    RSM is the Royal Saskatchewan Museum, a natural history and cultural museum in Regina, Saskatchewan, Canada.
  • D. RSM
    RSM is the abbreviation commonly used for the Royal Schools of Music, a group of prestigious UK conservatoires known for their music education and examination programs.
  • E. RSM
    RSM is the commonly used abbreviation for Renault Samsung Motors, a South Korean automobile manufacturer formerly affiliated with Renault.
  • 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af331108190b6b25ef8f386826e completed April 20, 2026, 1:32 p.m.
Created at: April 10, 2026, 1:36 p.m.