Triple

T3030673
Position Surface form Disambiguated ID Type / Status
Subject Marseille Provence Airport E82885 entity
Predicate IATAcode P418 FINISHED
Object MRS E129199 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: MRS | Statement: [Marseille Provence Airport, IATAcode, MRS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MRS
Context triple: [Marseille Provence Airport, IATAcode, MRS]
  • A. MRS chosen
    MRS is the Materials Research Society, a professional organization dedicated to advancing interdisciplinary materials science and engineering research and education.
  • B. MRSG
    MRSG is a U.S. Marine Corps organization that provides specialized logistical, administrative, and operational support to Marine Raider units within Marine Forces Special Operations Command (MARSOC).
  • C. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • D. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • E. MR
    MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9aecd384819085d15f701add7c44 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1debd245c819081eb2dec470f9156 completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.