Triple
T16972409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han Meilin |
E411718
|
entity |
| Predicate | designed |
P184
|
FINISHED |
| Object | Fuwa |
E115414
|
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: Fuwa | Statement: [Han Meilin, designed, Fuwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fuwa Context triple: [Han Meilin, designed, Fuwa]
-
A.
Fuwa
chosen
Fuwa are the five official mascots of the 2008 Beijing Olympic Games, each representing a different color of the Olympic rings and elements of Chinese culture and symbolism.
-
B.
Taku-shi
Taku-shi is a city located in Saga Prefecture on Japan’s Kyushu island, known for its historical sites and rural landscapes.
-
C.
Eifuku
Eifuku is a neighborhood in Suginami, Tokyo, Japan, known primarily as the area served by Eifukuchō Station.
-
D.
Yakumo
Yakumo is a residential neighborhood in Tokyo’s Meguro ward known for its quiet streets, schools, and proximity to parks and shopping areas.
-
E.
Chiwan
Chiwan is a coastal area in Shenzhen, China, known for its port facilities, historical sites, and role in the city’s maritime trade.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ae47f08190a13e98d20aba7f16 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d471d4248190acf40b6c11926a65 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.