Triple
T790001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Min |
E16890
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Mao Anlong |
E105098
|
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: Mao Anlong | Statement: [Li Min, hasRelative, Mao Anlong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mao Anlong Context triple: [Li Min, hasRelative, Mao Anlong]
-
A.
Mao Anlong
chosen
Mao Anlong was one of Mao Zedong’s sons, who died in childhood and is less documented than his more politically prominent siblings.
-
B.
Mao Anqing
Mao Anqing was the second son of Chinese Communist leader Mao Zedong, known for his work as a Russian-language translator and his relatively low political profile compared to his father.
-
C.
Mao Yuanxin
Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
-
D.
Mao Anying
Mao Anying was the eldest son of Chinese leader Mao Zedong, best known for his death while serving as a volunteer officer in the Korean War.
-
E.
Mao II
Mao II is a 1991 novel by Don DeLillo that explores themes of terrorism, mass media, and the diminishing power of the individual writer in a spectacle-driven world.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7841b0c8190859ecd247e32c6ec |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ccd40188190b5c4b9c3dc1f7554 |
completed | March 7, 2026, 12:40 p.m. |
Created at: March 1, 2026, 7:38 p.m.