Triple
T19955332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary at the Winter Olympics |
E479665
|
entity |
| Predicate | notableAchievement |
P477
|
FINISHED |
| Object | first Winter Olympic gold medal in short track speed skating men’s 5000 m relay at PyeongChang 2018 |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: first Winter Olympic gold medal in short track speed skating men’s 5000 m relay at PyeongChang 2018 | Statement: [Hungary at the Winter Olympics, notableAchievement, first Winter Olympic gold medal in short track speed skating men’s 5000 m relay at PyeongChang 2018]
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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65aefd9488190b8cdfa8543db8d31 |
completed | April 20, 2026, 4:57 p.m. |
Created at: April 10, 2026, 1:54 p.m.