Triple
T5551092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Song Ziwen |
E145526
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Song Ziwen |
E145526
|
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: Song Ziwen | Statement: [Song Ziwen, name, Song Ziwen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Song Ziwen Context triple: [Song Ziwen, name, Song Ziwen]
-
A.
Song Ziwen
chosen
Song Ziwen, better known as T. V. Soong, was a prominent Chinese financier and politician who served as a key economic architect and high-ranking official of the Republic of China during the early to mid-20th century.
-
B.
Zhu Xijuan
Zhu Xijuan is a Chinese actress best known for her leading role in the classic 1964 film "The Red Detachment of Women."
-
C.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
-
D.
Zhu Yawen
Zhu Yawen is a Chinese actor known for his roles in film and television dramas, particularly in military and historical series.
-
E.
Lu Lingzi
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe3e7788190aa5361b083197c17 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c028350bc08190a8b48893157b86a1 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:35 p.m.