Triple

T1503628
Position Surface form Disambiguated ID Type / Status
Subject Tandberg E33850 entity
Predicate tickerSymbol P1447 FINISHED
Object TAA
TAA is the stock ticker symbol for Tandberg, a Norwegian company known for its video conferencing and telecommunication solutions.
E171420 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: TAA | Statement: [Tandberg, tickerSymbol, TAA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAA
Context triple: [Tandberg, tickerSymbol, TAA]
  • A. TTA
    TTA (Telecommunications Technology Association) is South Korea’s primary standards organization for information and communication technologies, contributing to global telecom standards development.
  • B. TPA
    TPA is the three-letter IATA airport code for Tampa International Airport, a major commercial airport serving the Tampa Bay area in Florida, USA.
  • C. TPA
    TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
  • D. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • E. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • 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: TAA
Triple: [Tandberg, tickerSymbol, TAA]
Generated description
TAA is the stock ticker symbol for Tandberg, a Norwegian company known for its video conferencing and telecommunication solutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TAA
Target entity description: TAA is the stock ticker symbol for Tandberg, a Norwegian company known for its video conferencing and telecommunication solutions.
  • A. TTA
    TTA (Telecommunications Technology Association) is South Korea’s primary standards organization for information and communication technologies, contributing to global telecom standards development.
  • B. TPA
    TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
  • C. TPA
    TPA is the three-letter IATA airport code for Tampa International Airport, a major commercial airport serving the Tampa Bay area in Florida, USA.
  • D. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • E. TCA
    TCA is the commonly used abbreviation for the Technical Cooperation Administration, a former U.S. government agency responsible for administering foreign aid and technical assistance programs.
  • 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_69a885f352a4819099b24ff15489dede completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a8872fae4c81908e7d6961e6c5fa96 completed March 4, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1cb578e4819082d254462e10e4f0 completed March 8, 2026, 6:52 a.m.
NEDg Description generation batch_69ad1d34656481909949b4bfd83c6142 completed March 8, 2026, 6:54 a.m.
NED2 Entity disambiguation (via description) batch_69ad1dd7b34c8190b6957be2112506dd completed March 8, 2026, 6:57 a.m.
Created at: March 4, 2026, 7:24 p.m.