Triple
T790002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Min |
E16890
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Li Na |
E88883
|
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: Li Na | Statement: [Li Min, hasRelative, Li Na]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Li Na Context triple: [Li Min, hasRelative, Li Na]
-
A.
Li Na
chosen
Li Na is the daughter of Mao Zedong and Jiang Qing, known primarily for her connection to China’s former top leadership during the Mao era.
-
B.
Christine Mara
Christine Mara is a member of the Mara family, known for its long-time ownership and leadership of the New York Giants NFL franchise.
-
C.
Virginia Williams
Virginia Williams is an American woman best known as the wife of rapper Pusha T and for her low-key presence alongside his high-profile music career.
-
D.
Oksana Baiul
Oksana Baiul is a Ukrainian figure skater who became the 1994 Olympic ladies' singles champion and one of the sport's most celebrated performers.
-
E.
Lymari Nadal
Lymari Nadal is a Puerto Rican actress and producer best known for her role in the crime film "American Gangster."
- 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_69a67880f9608190b0676eb47ea99ca1 |
completed | March 3, 2026, 5:58 a.m. |
Created at: March 1, 2026, 7:38 p.m.