Triple

T14894939
Position Surface form Disambiguated ID Type / Status
Subject Telenet Group E359846 entity
Predicate tickerSymbol P1447 FINISHED
Object TNET
TNET is the stock ticker symbol for Telenet Group, a Belgian telecommunications and entertainment services provider.
E1125048 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: TNET | Statement: [Telenet Group, tickerSymbol, TNET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TNET
Context triple: [Telenet Group, tickerSymbol, TNET]
  • A. EETN
    EETN is the ICAO airport code for Lennart Meri Tallinn Airport, the main international airport serving Tallinn, Estonia.
  • B. Nitelink
    Nitelink is Dublin’s late-night bus service network, providing after-hours public transport on key routes across the city and suburbs.
  • C. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • D. TEN: The Enthusiast Network
    TEN: The Enthusiast Network is a media company specializing in automotive and enthusiast content across magazines, digital platforms, and events.
  • 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: TNET
Triple: [Telenet Group, tickerSymbol, TNET]
Generated description
TNET is the stock ticker symbol for Telenet Group, a Belgian telecommunications and entertainment services provider.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TNET
Target entity description: TNET is the stock ticker symbol for Telenet Group, a Belgian telecommunications and entertainment services provider.
  • A. EETN
    EETN is the ICAO airport code for Lennart Meri Tallinn Airport, the main international airport serving Tallinn, Estonia.
  • B. Nitelink
    Nitelink is Dublin’s late-night bus service network, providing after-hours public transport on key routes across the city and suburbs.
  • C. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • D. TEN: The Enthusiast Network
    TEN: The Enthusiast Network is a media company specializing in automotive and enthusiast content across magazines, digital platforms, and events.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded6070b248190be8f4f91a0c0b1f3 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b679fb081908cf8f41acfba3b99 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6cc2ccb0819081e32dc9d2e3973a completed May 8, 2026, 11:07 p.m.
NED2 Entity disambiguation (via description) batch_69fe6d9e9a648190920206c8f75cae2e completed May 8, 2026, 11:11 p.m.
Created at: April 10, 2026, 2:10 a.m.