Triple

T9817612
Position Surface form Disambiguated ID Type / Status
Subject Rovereto E238447 entity
Predicate knownFor P22 FINISHED
Object MART
MART is a prominent modern and contemporary art museum in Rovereto, Italy, renowned for its extensive collections and striking contemporary architecture.
 E823446 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: MART | Statement: [Rovereto, knownFor, MART]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MART
Context triple: [Rovereto, knownFor, MART]
  • A. Mart.
    Mart. is the standard botanical author abbreviation for the German botanist and explorer Carl Friedrich Philipp von Martius, known for his extensive work on Brazilian flora.
  • B. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • C. MAUR
    MAUR is the Management Authority for Urban Railways, a government body responsible for overseeing the development and operation of urban rail transit systems.
  • D. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • E. MARCI
    MARCI is a wide-angle camera aboard NASA's Mars Reconnaissance Orbiter that continuously monitors and maps Martian weather and atmospheric conditions.
  • 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: MART
Triple: [Rovereto, knownFor, MART]
Generated description
MART is a prominent modern and contemporary art museum in Rovereto, Italy, renowned for its extensive collections and striking contemporary architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MART
Target entity description: MART is a prominent modern and contemporary art museum in Rovereto, Italy, renowned for its extensive collections and striking contemporary architecture.
  • A. Mart.
    Mart. is the standard botanical author abbreviation for the German botanist and explorer Carl Friedrich Philipp von Martius, known for his extensive work on Brazilian flora.
  • B. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • C. MAUR
    MAUR is the Management Authority for Urban Railways, a government body responsible for overseeing the development and operation of urban rail transit systems.
  • D. MAR
    MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
  • E. MARCI
    MARCI is a wide-angle camera aboard NASA's Mars Reconnaissance Orbiter that continuously monitors and maps Martian weather and atmospheric conditions.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f5bfa481908a2d2cb3f3d7d585 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc70d1188190820a49766699b94a completed April 5, 2026, 2:44 a.m.
NEDg Description generation batch_69d1cf9669308190a58e58b86e652801 completed April 5, 2026, 2:57 a.m.
NED2 Entity disambiguation (via description) batch_69d1d0034dc081908182e3f873a2c584 completed April 5, 2026, 2:59 a.m.
Created at: March 30, 2026, 8:30 p.m.