Triple
T697007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 Winter Olympics |
E13914
|
entity |
| Predicate | mascot |
P52
|
FINISHED |
| Object |
Bing Dwen Dwen
Bing Dwen Dwen is the panda-shaped official mascot of the 2022 Beijing Winter Olympics, known for its ice-suit design and playful, friendly appearance.
|
E85579
|
NE FINISHED |
How this triple was built (4 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: Bing Dwen Dwen | Statement: [2022 Winter Olympics, mascot, Bing Dwen Dwen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bing Dwen Dwen Context triple: [2022 Winter Olympics, mascot, Bing Dwen Dwen]
-
A.
Princess Kiko
Princess Kiko is a member of Japan’s imperial family, known as the wife of Crown Prince Fumihito and mother of Prince Hisahito, the only male heir of his generation.
-
B.
Snowlets
Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
-
C.
Rudolph
Rudolph is the legendary red-nosed reindeer from Christmas folklore who guides Santa Claus’s sleigh through the night.
-
D.
Shenwa
Shenwa is a Zenati Berber language spoken by a small community in the Chenoua (Shenwa) region of northern Algeria.
-
E.
Jin
Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bing Dwen Dwen Triple: [2022 Winter Olympics, mascot, Bing Dwen Dwen]
Generated description
Bing Dwen Dwen is the panda-shaped official mascot of the 2022 Beijing Winter Olympics, known for its ice-suit design and playful, friendly appearance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bing Dwen Dwen Target entity description: Bing Dwen Dwen is the panda-shaped official mascot of the 2022 Beijing Winter Olympics, known for its ice-suit design and playful, friendly appearance.
-
A.
Princess Kiko
Princess Kiko is a member of Japan’s imperial family, known as the wife of Crown Prince Fumihito and mother of Prince Hisahito, the only male heir of his generation.
-
B.
Snowlets
Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
-
C.
Rudolph
Rudolph is the legendary red-nosed reindeer from Christmas folklore who guides Santa Claus’s sleigh through the night.
-
D.
Shenwa
Shenwa is a Zenati Berber language spoken by a small community in the Chenoua (Shenwa) region of northern Algeria.
-
E.
Jin
Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
- F. None of above. chosen
Provenance (5 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0c8055881909565ebde2be8fd7a |
completed | March 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dca9aa9c8190a113e782988aa7f8 |
completed | March 2, 2026, 6:53 p.m. |
| NEDg | Description generation | batch_69a5e70510908190bcbd1c46629d05f5 |
completed | March 2, 2026, 7:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a60989aac08190a324c8d9889086f5 |
completed | March 2, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:36 p.m.