Triple
T2754677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canada women's national under-20 soccer team |
E61070
|
entity |
| Predicate | fifaCode |
P6278
|
FINISHED |
| Object | CAN |
E86792
|
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: [Canada women's national under-20 soccer team, fifaCode, CAN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAN Context triple: [Canada women's national under-20 soccer team, fifaCode, 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
chosen
CAN is the FIFA country code for Canada, the North American nation whose teams and players participate in international soccer competitions.
-
C.
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.
-
D.
CAN
CAN is the three-letter IATA airport code for Guangzhou Baiyun International Airport, a major air transport hub in southern China.
-
E.
CAC
CAC is the Computing Accreditation Commission, a specialized body that accredits computing-related degree programs to ensure they meet established quality and professional standards.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb7073d081909da84b21015972f2 |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc040c5f08190898e81938afe6884 |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:56 p.m.