Triple

T9875854
Position Surface form Disambiguated ID Type / Status
Subject Palais Omnisports de Paris-Bercy E240069 entity
Predicate renovationArchitect P6475 FINISHED
Object DVVD
DVVD is an architectural firm known for its role in the renovation of major public venues such as the Palais Omnisports de Paris-Bercy in Paris.
 E826454 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: DVVD | Statement: [Palais Omnisports de Paris-Bercy, renovationArchitect, DVVD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DVVD
Context triple: [Palais Omnisports de Paris-Bercy, renovationArchitect, DVVD]
  • A. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • B. VD
    VD is the vehicle registration code for the Swiss canton of Vaud.
  • C. VVI
    VVI is the IATA airport code for Viru Viru International Airport, the main international gateway serving Santa Cruz de la Sierra, Bolivia.
  • D. VDNKh
    VDNKh is a vast exhibition and amusement complex in Moscow known for its grand Soviet-era pavilions, monuments, and cultural attractions.
  • E. VDY
    VDY is the IATA airport code for Jindal Vijaynagar Airport in Karnataka, India.
  • 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: DVVD
Triple: [Palais Omnisports de Paris-Bercy, renovationArchitect, DVVD]
Generated description
DVVD is an architectural firm known for its role in the renovation of major public venues such as the Palais Omnisports de Paris-Bercy in Paris.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DVVD
Target entity description: DVVD is an architectural firm known for its role in the renovation of major public venues such as the Palais Omnisports de Paris-Bercy in Paris.
  • A. VDV
    VDV is the elite airborne branch of Russia’s armed forces, known for rapid-deployment paratrooper and air-assault operations.
  • B. VD
    VD is the vehicle registration code for the Swiss canton of Vaud.
  • C. VVI
    VVI is the IATA airport code for Viru Viru International Airport, the main international gateway serving Santa Cruz de la Sierra, Bolivia.
  • D. VDNKh
    VDNKh is a vast exhibition and amusement complex in Moscow known for its grand Soviet-era pavilions, monuments, and cultural attractions.
  • E. VDY
    VDY is the IATA airport code for Jindal Vijaynagar Airport in Karnataka, India.
  • 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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3f9d82c81908afb4977ce4e3e4a completed April 2, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e47b62388190a033743376500375 completed April 5, 2026, 4:26 a.m.
NEDg Description generation batch_69d1e5d0da7081908e14fe4bc6623ea5 completed April 5, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_69d1e6af89f88190abe63f8172182f58 completed April 5, 2026, 4:35 a.m.
Created at: March 30, 2026, 8:37 p.m.