Triple
T4119969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 Winter Paralympics |
E92586
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object | Shuey Rhon Rhon |
E389359
|
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: Shuey Rhon Rhon | Statement: [2022 Winter Paralympics, mascot, Shuey Rhon Rhon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shuey Rhon Rhon Context triple: [2022 Winter Paralympics, mascot, Shuey Rhon Rhon]
-
A.
Shuey Rhon Rhon
chosen
Shuey Rhon Rhon is the lantern child mascot of the Beijing 2022 Winter Paralympic Games, symbolizing warmth, hope, and the Paralympic spirit.
-
B.
Ruabon
Ruabon is a village and community in Wrexham County Borough, Wales, historically known for its coal mining and brickmaking industries and its location on key transport routes.
-
C.
Rhun
Rhûn is an eastern region of J.R.R. Tolkien’s Middle-earth, largely unexplored in the stories and home to various distant and often hostile peoples.
-
D.
Shifnal
Shifnal is a small market town in Shropshire, England, known for its historic buildings and proximity to Telford.
-
E.
Schaumainkai
Schaumainkai is a prominent riverside street along the south bank of the Main River in Frankfurt, Germany, known for its concentration of major museums and cultural institutions.
- 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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af01f5ed3881908bda4dbed497beba |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576ae8ef08190ba2adcbd2bbe8d35 |
completed | March 14, 2026, 2:54 p.m. |
Created at: March 9, 2026, 3:41 p.m.