Triple

T19676157
Position Surface form Disambiguated ID Type / Status
Subject Mobilier National E472457 entity
Predicate shortName P43 FINISHED
Object MN
MN is the abbreviated name for Mobilier National, the French national agency responsible for preserving, managing, and furnishing state-owned collections of furniture and decorative arts.
 E1390500 NE FINISHED

How this triple was built (4 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: MN | Statement: [Mobilier National, shortName, MN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MN
Context triple: [Mobilier National, shortName, MN]
  • A. MN
    MN is the standard two-letter postal abbreviation for the U.S. state of Minnesota.
  • B. MN
    MN is the abbreviated designation commonly used for a Monumento Nacional, a protected national monument of significant cultural or historical value.
  • C. MN
    MN is the vehicle registration code used on license plates for vehicles registered in Douglas and the rest of the Isle of Man.
  • D. MN
    MN was the official abbreviation for the Hungarian People’s Army, the armed forces of the Hungarian People's Republic during the socialist era.
  • E. NM
    NM is the standard two-letter U.S. postal abbreviation for the state of New Mexico.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MN
Triple: [Mobilier National, shortName, MN]
Generated description
MN is the abbreviated name for Mobilier National, the French national agency responsible for preserving, managing, and furnishing state-owned collections of furniture and decorative arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MN
Target entity description: MN is the abbreviated name for Mobilier National, the French national agency responsible for preserving, managing, and furnishing state-owned collections of furniture and decorative arts.
  • A. MN
    MN is the vehicle registration code used on license plates for vehicles registered in Douglas and the rest of the Isle of Man.
  • B. MN
    MN was the official abbreviation for the Hungarian People’s Army, the armed forces of the Hungarian People's Republic during the socialist era.
  • C. MN
    MN is the standard two-letter postal abbreviation for the U.S. state of Minnesota.
  • D. MN
    MN is the abbreviated designation commonly used for a Monumento Nacional, a protected national monument of significant cultural or historical value.
  • E. NM
    NM is the standard two-letter U.S. postal abbreviation for the state of New Mexico.
  • F. None of above. chosen

Provenance (5 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bbea8c8190b0ad841d95068e0e completed April 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0787c261808190b4bf53d0a7ecd54b completed May 15, 2026, 8:53 p.m.
NEDg Description generation batch_6a0789df479881909750ae3fcf509dd9 completed May 15, 2026, 9:02 p.m.
NED2 Entity disambiguation (via description) batch_6a078a70157081908b7137984dc05e42 completed May 15, 2026, 9:04 p.m.
Created at: April 10, 2026, 1:45 p.m.