Triple

T13477127
Position Surface form Disambiguated ID Type / Status
Subject Mercedes-AMG F1 W06 Hybrid E318277 entity
Predicate energyRecoverySystem P44376 FINISHED
Object ERS
ERS is a hybrid Formula 1 power unit component that recovers and stores energy from braking and exhaust heat to provide additional electrical power for improved performance and efficiency.
 E1043489 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: ERS | Statement: [Mercedes-AMG F1 W06 Hybrid, energyRecoverySystem, ERS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ERS
Context triple: [Mercedes-AMG F1 W06 Hybrid, energyRecoverySystem, ERS]
  • A. ERS
    ERS is the principal economic and social science research agency of the U.S. Department of Agriculture, providing data and analysis on agriculture, food, the environment, and rural development.
  • B. ERS
    ERS is the abbreviation for the Elmira River Sharks, a professional ice hockey team based in Elmira, New York.
  • C. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • D. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • E. ER
    ER is the zone code for Eastern Railway, one of the major railway zones of Indian Railways headquartered in Kolkata.
  • 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: ERS
Triple: [Mercedes-AMG F1 W06 Hybrid, energyRecoverySystem, ERS]
Generated description
ERS is a hybrid Formula 1 power unit component that recovers and stores energy from braking and exhaust heat to provide additional electrical power for improved performance and efficiency.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ERS
Target entity description: ERS is a hybrid Formula 1 power unit component that recovers and stores energy from braking and exhaust heat to provide additional electrical power for improved performance and efficiency.
  • A. ERS
    ERS is the principal economic and social science research agency of the U.S. Department of Agriculture, providing data and analysis on agriculture, food, the environment, and rural development.
  • B. ERS
    ERS is the abbreviation for the Elmira River Sharks, a professional ice hockey team based in Elmira, New York.
  • C. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • D. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • E. ER
    ER is the IATA airline designator assigned to SereneAir, a Pakistani low-cost carrier.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf2551b48190a074fd256791742d completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f746318490819095a5697cc396eb6f completed May 3, 2026, 12:57 p.m.
NEDg Description generation batch_69f74ce7d64c8190ba9f1ed59af4bd9e completed May 3, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69f74d5389f08190826f0e550c8bb6c2 completed May 3, 2026, 1:27 p.m.
Created at: April 9, 2026, 9:42 p.m.