Triple

T8318131
Position Surface form Disambiguated ID Type / Status
Subject Munich Re E194756 entity
Predicate tickerSymbol P1447 FINISHED
Object MUV2
MUV2 is the stock ticker symbol for Munich Re, a leading global reinsurance company based in Germany.
 E725737 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: MUV2 | Statement: [Munich Re, tickerSymbol, MUV2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MUV2
Context triple: [Munich Re, tickerSymbol, MUV2]
  • A. MIV
    MIV is a specialized market segment of Borsa Italiana dedicated to the listing and trading of investment vehicles such as closed-end funds and investment companies.
  • B. Muevelo
    Muevelo is a song best known as a high-energy Latin dance track whose title translates to “Move it.”
  • C. BMUV
    BMUV is the German federal ministry responsible for environmental protection, nature conservation, nuclear safety, and consumer protection policy.
  • D. MIA Mover
    The MIA Mover is an automated people mover system that transports passengers between Miami International Airport and the nearby Miami Intermodal Center transportation hub.
  • E. MVU
    MVU (Model-View-Update) is an architectural pattern for building user interfaces that emphasizes a unidirectional data flow, immutable state, and a clear separation between state, view rendering, and update logic.
  • 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: MUV2
Triple: [Munich Re, tickerSymbol, MUV2]
Generated description
MUV2 is the stock ticker symbol for Munich Re, a leading global reinsurance company based in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MUV2
Target entity description: MUV2 is the stock ticker symbol for Munich Re, a leading global reinsurance company based in Germany.
  • A. MIV
    MIV is a specialized market segment of Borsa Italiana dedicated to the listing and trading of investment vehicles such as closed-end funds and investment companies.
  • B. Muevelo
    Muevelo is a song best known as a high-energy Latin dance track whose title translates to “Move it.”
  • C. BMUV
    BMUV is the German federal ministry responsible for environmental protection, nature conservation, nuclear safety, and consumer protection policy.
  • D. MIA Mover
    The MIA Mover is an automated people mover system that transports passengers between Miami International Airport and the nearby Miami Intermodal Center transportation hub.
  • E. MVU
    MVU (Model-View-Update) is an architectural pattern for building user interfaces that emphasizes a unidirectional data flow, immutable state, and a clear separation between state, view rendering, and update logic.
  • 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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f630ea881909fb639383e60aee9 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd9596891c81909296050d0a8117ca completed April 1, 2026, 10 p.m.
NEDg Description generation batch_69cdab5f30b0819080136084d81774a9 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2d365e48190a766ca959ce56b19 completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:55 p.m.