Triple
T22244837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA country code system |
E549814
|
entity |
| Predicate | hasExampleCode |
P30248
|
FINISHED |
| Object | KOR |
—
|
NE NERFINISHED |
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: KOR | Statement: [FIFA country code system, hasExampleCode, KOR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KOR Context triple: [FIFA country code system, hasExampleCode, KOR]
-
A.
KOR
chosen
KOR is the FIFA country code representing the South Korea national football team in international competitions.
-
B.
KOR
KOR is the ICAO airline designator assigned to Air Koryo, the state-owned national carrier of North Korea.
-
C.
Kor
Kor is a prominent Klingon warrior and commander from the Star Trek franchise, known as one of the earliest and most iconic Klingon characters in the series.
-
D.
KORL
KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
-
E.
KR
KR is the stock ticker symbol for The Kroger Co., one of the largest supermarket chains in the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f132170e5081909b9dbb204abf2a45 |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 16, 2026, 8:38 p.m.