Triple

T7428257
Position Surface form Disambiguated ID Type / Status
Subject Tandberg E171420 entity
Predicate stockTicker P1447 FINISHED
Object TAA E171420 NE FINISHED

How this triple was built (2 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, stockTicker, TAA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TAA
Context triple: [Tandberg, stockTicker, TAA]
  • A. TAA chosen
    TAA is the stock ticker symbol for Tandberg, a Norwegian company known for its video conferencing and telecommunication solutions.
  • B. Taa
    Taa, also known as ǃXóõ, is a highly complex Khoisan language of southern Africa noted for having one of the largest consonant inventories and extensive use of click sounds.
  • C. TTA
    TTA (Telecommunications Technology Association) is South Korea’s primary standards organization for information and communication technologies, contributing to global telecom standards development.
  • D. TTA
    TTA is the IATA airport code for Raleigh Executive Jetport, a general aviation airport serving the Raleigh, North Carolina area.
  • E. TAE
    TAE is the station code for Terminal Aérea, a Mexico City Metro station serving passengers traveling to and from the city’s international airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c68a63491881909281f73d4d5643bf completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f306bfe481909f99f6792de95ffc completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81f0e28e88190805108dff740dda3 completed March 28, 2026, 6:33 p.m.
Created at: March 27, 2026, 3:12 p.m.