Triple
T15591351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teng |
E374749
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Teng Yu-ting
Teng Yu-ting is a Taiwanese taekwondo practitioner known for competing at the international level, including major multi-sport events.
|
E1180665
|
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: Teng Yu-ting | Statement: [Teng, hasNotableBearer, Teng Yu-ting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teng Yu-ting Context triple: [Teng, hasNotableBearer, Teng Yu-ting]
-
A.
Teng Yu-hua
Teng Yu-hua is a person notable for bearing the Chinese surname Teng.
-
B.
Teng Yu-fan
Teng Yu-fan is a person notable for bearing the Chinese surname Teng.
-
C.
Teng Yu-hsien
Teng Yu-hsien was a pioneering Taiwanese composer often regarded as the father of modern Taiwanese folk and popular music.
-
D.
Yen Yu-yun
Yen Yu-yun was a Chinese socialite and diplomat’s wife best known as the spouse of prominent Chinese statesman V. K. Wellington Koo.
-
E.
Ting-Ting
Ting-Ting is one of the Emperor of China’s daughters and a poised, duty-bound princess who accompanies Mulan and Shang on their diplomatic journey in Disney’s animated sequel "Mulan II."
- 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: Teng Yu-ting Triple: [Teng, hasNotableBearer, Teng Yu-ting]
Generated description
Teng Yu-ting is a Taiwanese taekwondo practitioner known for competing at the international level, including major multi-sport events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teng Yu-ting Target entity description: Teng Yu-ting is a Taiwanese taekwondo practitioner known for competing at the international level, including major multi-sport events.
-
A.
Teng Yu-hua
Teng Yu-hua is a person notable for bearing the Chinese surname Teng.
-
B.
Teng Yu-fan
Teng Yu-fan is a person notable for bearing the Chinese surname Teng.
-
C.
Teng Yu-hsien
Teng Yu-hsien was a pioneering Taiwanese composer often regarded as the father of modern Taiwanese folk and popular music.
-
D.
Yen Yu-yun
Yen Yu-yun was a Chinese socialite and diplomat’s wife best known as the spouse of prominent Chinese statesman V. K. Wellington Koo.
-
E.
Ting-Ting
Ting-Ting is one of the Emperor of China’s daughters and a poised, duty-bound princess who accompanies Mulan and Shang on their diplomatic journey in Disney’s animated sequel "Mulan II."
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4b903c8190a35f9267cb38e721 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa124e7d48190ac25e9541dea0122 |
completed | May 9, 2026, 9:03 p.m. |
| NEDg | Description generation | batch_69ffa1a919b481909c0007411535588b |
completed | May 9, 2026, 9:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffa4212ca88190973d68dfbd8e103a |
completed | May 9, 2026, 9:16 p.m. |
Created at: April 10, 2026, 4:11 a.m.