Triple

T7968066
Position Surface form Disambiguated ID Type / Status
Subject ZGGG E185254 entity
Predicate associatedIataCode P2569 FINISHED
Object CAN E185253 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: CAN | Statement: [ZGGG, associatedIataCode, CAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CAN
Context triple: [ZGGG, associatedIataCode, CAN]
  • A. CAN
    CAN is the standard international abbreviation for the Canada men's national ice hockey team, one of the most successful and historically dominant teams in world ice hockey.
  • B. CAN
    CAN is a South American regional integration organization that promotes economic and social cooperation among its member countries, including Bolivia, Colombia, Ecuador, and Peru.
  • C. CAN chosen
    CAN is the three-letter IATA airport code for Guangzhou Baiyun International Airport, a major air transport hub in southern China.
  • D. CAN
    CAN is the FIFA country code for Canada, the North American nation whose teams and players participate in international soccer competitions.
  • E. CAN bus
    CAN bus is a robust automotive serial communication network standard that allows microcontrollers and devices to communicate with each other without a host computer, widely used in vehicles and industrial systems.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bd06ee081908c5080003fb7b8f7 completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc566afad88190b53f228d836619de completed March 31, 2026, 11:19 p.m.
Created at: March 30, 2026, 5:13 p.m.