Triple
T17258906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lu Lingjia |
E418957
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Lu Lingzi |
—
|
NE NERFINISHED |
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: Lu Lingzi | Statement: [Lu Lingjia, relative, Lu Lingzi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lu Lingzi Context triple: [Lu Lingjia, relative, Lu Lingzi]
-
A.
Lu Lingzi
chosen
Lu Lingzi was a Chinese graduate student at Boston University who was killed in the 2013 Boston Marathon bombing.
-
B.
Lu Lingjia
Lu Lingjia is a Chinese individual known primarily as a relative of Lu Lingzi, one of the victims of the 2013 Boston Marathon bombing.
-
C.
Li Ling
Li Ling was a Han dynasty military general best known for his ill-fated campaign against the Xiongnu and subsequent controversial surrender that sparked political turmoil in the Han court.
-
D.
Yao Ling
Yao Ling is known as the former spouse of Ren Zhengfei, the founder of Chinese telecommunications giant Huawei.
-
E.
Li Jingxi
Li Jingxi was a Chinese politician and statesman who briefly served as premier during the early years of the Republic of China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6ea7588190a94d222504a8cef5 |
completed | April 19, 2026, 1:22 a.m. |
Created at: April 10, 2026, 5:39 a.m.