Triple
T8856168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuo Lin |
E210761
|
entity |
| Predicate | spouseOfPosition |
P26554
|
FINISHED |
| Object | Paramount leader of China |
—
|
LITERAL 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: Paramount leader of China | Statement: [Zhuo Lin, spouseOfPosition, Paramount leader of China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfPosition Context triple: [Zhuo Lin, spouseOfPosition, Paramount leader of China]
-
A.
spouseOffice
chosen
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
B.
spouseOfHead
Indicates that one person is the married partner of the individual who holds the position of head (e.g., head of a household, organization, or state).
-
C.
spouseOfOfficeHolderJurisdiction
Indicates that one person is the spouse of a public office holder, with the relationship specifically tied to the jurisdiction in which that office is held.
-
D.
spouseOfHeadOfState
Indicates that one person is the spouse (married partner) of a head of state.
-
E.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
- F. None of above.
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_69ca838a424c8190b1ecac115c2927e7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e259248190abd334bbfcdcb955 |
completed | April 1, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69cc5c279ea481908c71756f694b66bf |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:50 p.m.