Triple
T8656878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yen Chia-kan |
E205441
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Chia-kan
Chia-kan is the given name of Yen Chia-kan, who served as President of the Republic of China (Taiwan) in the 1970s.
|
E748739
|
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: Chia-kan | Statement: [Yen Chia-kan, givenName, Chia-kan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chia-kan Context triple: [Yen Chia-kan, givenName, Chia-kan]
-
A.
Tocho
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
-
B.
Hacha-Kekan
Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
-
C.
Chimariko
Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
-
D.
Hanacaraka
Hanacaraka is the traditional Javanese writing system used historically on the island of Java for literary, religious, and everyday texts.
-
E.
Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
- 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: Chia-kan Triple: [Yen Chia-kan, givenName, Chia-kan]
Generated description
Chia-kan is the given name of Yen Chia-kan, who served as President of the Republic of China (Taiwan) in the 1970s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chia-kan Target entity description: Chia-kan is the given name of Yen Chia-kan, who served as President of the Republic of China (Taiwan) in the 1970s.
-
A.
Tocho
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
-
B.
Hacha-Kekan
Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
-
C.
Chimariko
Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
-
D.
Hanacaraka
Hanacaraka is the traditional Javanese writing system used historically on the island of Java for literary, religious, and everyday texts.
-
E.
Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484569788190aa41395854684e6f |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccec941881908263cd3205f10ccd |
completed | April 2, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69cece8c4bdc8190988990c675f50f86 |
completed | April 2, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecf3a0e78819082cc7c43eceae309 |
completed | April 2, 2026, 8:19 p.m. |
Created at: March 30, 2026, 6:30 p.m.