Triple

T1286226
Position Surface form Disambiguated ID Type / Status
Subject Max Planck Society E27439 entity
Predicate shortName P43 FINISHED
Object MPG
MPG is the commonly used abbreviation for the Max Planck Society, Germany’s leading network of research institutes in the natural sciences, life sciences, and humanities.
 E146435 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: MPG | Statement: [Max Planck Society, shortName, MPG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MPG
Context triple: [Max Planck Society, shortName, MPG]
  • A. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • B. MPR
    MPR is the Indonesian acronym for the People's Consultative Assembly, the country's highest constitutional body responsible for key legislative and constitutional functions.
  • C. Mobil
    Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
  • D. BMP
    BMP is the Basic Multilingual Plane of Unicode, the primary block of code points that encodes the most commonly used characters from modern and many historic writing systems.
  • E. H.264
    H.264 is a widely used video compression standard known for delivering high-quality video at relatively low bitrates, commonly employed in streaming, broadcasting, and video recording.
  • 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: MPG
Triple: [Max Planck Society, shortName, MPG]
Generated description
MPG is the commonly used abbreviation for the Max Planck Society, Germany’s leading network of research institutes in the natural sciences, life sciences, and humanities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MPG
Target entity description: MPG is the commonly used abbreviation for the Max Planck Society, Germany’s leading network of research institutes in the natural sciences, life sciences, and humanities.
  • A. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • B. MPR
    MPR is the Indonesian acronym for the People's Consultative Assembly, the country's highest constitutional body responsible for key legislative and constitutional functions.
  • C. Mobil
    Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
  • D. BMP
    BMP is the Basic Multilingual Plane of Unicode, the primary block of code points that encodes the most commonly used characters from modern and many historic writing systems.
  • E. H.264
    H.264 is a widely used video compression standard known for delivering high-quality video at relatively low bitrates, commonly employed in streaming, broadcasting, and video recording.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b85eb48190a8b61dc397fa6390 completed March 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca3004b648190a4148b0421699bf9 completed March 7, 2026, 10:13 p.m.
NEDg Description generation batch_69aca3a539848190a17e8bd578bc237a completed March 7, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69aca4158bbc8190bd1f5799715e3e4c completed March 7, 2026, 10:17 p.m.
Created at: March 1, 2026, 7:51 p.m.