Triple

T3650804
Position Surface form Disambiguated ID Type / Status
Subject Taiwan Taoyuan International Airport E77411 entity
Predicate hasAirportCode P6089 FINISHED
Object TPE E22639 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: TPE | Statement: [Taiwan Taoyuan International Airport, hasAirportCode, TPE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TPE
Context triple: [Taiwan Taoyuan International Airport, hasAirportCode, TPE]
  • A. TPE chosen
    TPE is the three-letter IOC and international sporting code used to represent Chinese Taipei (Taiwan) in global competitions and events.
  • B. TPU
    A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
  • 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. 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.
  • E. T&P
    T&P is the common abbreviation for the historic Texas and Pacific Railway, a major railroad that operated across Texas and the southwestern United States.
  • 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_69ad85def5cc8190863dccf55a18bebb completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc39303bc819090725643e53a96d6 completed March 8, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b488394aa48190b91985aa912cf733 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:24 p.m.