Triple
T17111513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsang |
E415236
|
entity |
| Predicate | hasVariantRomanization |
P5800
|
FINISHED |
| Object | Tseng |
E415235
|
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: Tseng | Statement: [Tsang, hasVariantRomanization, Tseng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tseng Context triple: [Tsang, hasVariantRomanization, Tseng]
-
A.
Tseng
chosen
Tseng is a romanized Chinese surname, commonly representing the same family name as Zeng in alternative transliteration systems.
-
B.
Tseng Wen-hui
Tseng Wen-hui is a Taiwanese public figure best known as the wife of former President Lee Teng-hui and for serving as First Lady during Taiwan’s transition to democracy.
-
C.
Tung-Yen
Tung-Yen is the Chinese given name of T.Y. Lin, the influential civil engineer renowned for his pioneering work in modern prestressed concrete design.
-
D.
Zine Tseng
Zine Tseng is an actress best known for playing the pivotal character Ye Wenjie in the television adaptation of Liu Cixin’s science-fiction novel "The Three-Body Problem."
-
E.
Tai Jia
Tai Jia was an early king of the Shang dynasty in ancient China, traditionally regarded as a grandson and successor of the dynasty’s founder, Tang.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2a7f2c81908eb19594b6accab7 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a062d7c81908fe8cdc9e4637168 |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:35 a.m.