Triple

T14441487
Position Surface form Disambiguated ID Type / Status
Subject CEC Control E358091 entity
Predicate mayBeBrandedAs P11989 FINISHED
Object AnyNet
AnyNet is a brand name used for CEC Control’s networking and connectivity solutions.
E1099091 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: AnyNet | Statement: [CEC Control, mayBeBrandedAs, AnyNet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AnyNet
Context triple: [CEC Control, mayBeBrandedAs, AnyNet]
  • A. ANET
    ANET is the stock ticker symbol for Arista Networks, a leading provider of cloud networking solutions for large data centers and computing environments.
  • B. AVE network
    The AVE network is Spain’s high-speed rail system that connects major cities across the country with fast, long-distance train services.
  • C. Network
    Network is a 1976 satirical drama film directed by Sidney Lumet that critiques television news and media sensationalism.
  • D. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • E. R-net
    R-net is a high-quality Dutch public transport network brand that unifies and standardizes premium bus, tram, metro, and train services across several regions in the Netherlands.
  • 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: AnyNet
Triple: [CEC Control, mayBeBrandedAs, AnyNet]
Generated description
AnyNet is a brand name used for CEC Control’s networking and connectivity solutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: AnyNet
Target entity description: AnyNet is a brand name used for CEC Control’s networking and connectivity solutions.
  • A. ANET
    ANET is the stock ticker symbol for Arista Networks, a leading provider of cloud networking solutions for large data centers and computing environments.
  • B. AVE network
    The AVE network is Spain’s high-speed rail system that connects major cities across the country with fast, long-distance train services.
  • C. Network
    Network is a 1976 satirical drama film directed by Sidney Lumet that critiques television news and media sensationalism.
  • D. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • E. R-net
    R-net is a high-quality Dutch public transport network brand that unifies and standardizes premium bus, tram, metro, and train services across several regions in the Netherlands.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914c1398819090fa2a74d257ba3e completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bda6ee88190aeec77092eb3576a completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5d8c0e4881908dac3fb5a5ac79bc completed May 8, 2026, 3:50 a.m.
NED2 Entity disambiguation (via description) batch_69fd5e46c184819092ebb2b5aad28125 completed May 8, 2026, 3:53 a.m.
Created at: April 10, 2026, 1:18 a.m.