Triple

T18644658
Position Surface form Disambiguated ID Type / Status
Subject Lindsay Corporation E455772 entity
Predicate brand P1500 FINISHED
Object FieldNET
FieldNET is a remote irrigation management and monitoring platform developed by Lindsay Corporation for agricultural water and equipment control.
 E1335205 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: FieldNET | Statement: [Lindsay Corporation, brand, FieldNET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FieldNET
Context triple: [Lindsay Corporation, brand, FieldNET]
  • A. TNET
    TNET is the stock ticker symbol for Telenet Group, a Belgian telecommunications and entertainment services provider.
  • B. SNET
    SNET is El Salvador’s national agency responsible for territorial studies, including monitoring and research on geology, meteorology, and related environmental risks.
  • C. FleetNet America
    FleetNet America is a U.S.-based provider of fleet maintenance and emergency roadside repair services for commercial vehicles, operating as part of Cox Automotive.
  • D. Nitelink
    Nitelink is Dublin’s late-night bus service network, providing after-hours public transport on key routes across the city and suburbs.
  • E. AnyNet
    AnyNet is a brand name used for CEC Control’s networking and connectivity solutions.
  • 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: FieldNET
Triple: [Lindsay Corporation, brand, FieldNET]
Generated description
FieldNET is a remote irrigation management and monitoring platform developed by Lindsay Corporation for agricultural water and equipment control.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FieldNET
Target entity description: FieldNET is a remote irrigation management and monitoring platform developed by Lindsay Corporation for agricultural water and equipment control.
  • A. TNET
    TNET is the stock ticker symbol for Telenet Group, a Belgian telecommunications and entertainment services provider.
  • B. SNET
    SNET is El Salvador’s national agency responsible for territorial studies, including monitoring and research on geology, meteorology, and related environmental risks.
  • C. FleetNet America
    FleetNet America is a U.S.-based provider of fleet maintenance and emergency roadside repair services for commercial vehicles, operating as part of Cox Automotive.
  • D. Nitelink
    Nitelink is Dublin’s late-night bus service network, providing after-hours public transport on key routes across the city and suburbs.
  • E. AnyNet
    AnyNet is a brand name used for CEC Control’s networking and connectivity solutions.
  • 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5500c36188190bfdd7aca73f3c006 completed April 19, 2026, 9:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a050d865fc48190a11ed96ebfdca50d completed May 13, 2026, 11:47 p.m.
NEDg Description generation batch_6a051058f5788190b782a39feb7f6111 completed May 13, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a0510fc0d1081908970c91357bb3444 completed May 14, 2026, 12:02 a.m.
Created at: April 10, 2026, 11:47 a.m.