Triple
T21150195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 倪桂珍 |
E521166
|
entity |
| Predicate | 宗教背景 |
P127992
|
FINISHED |
| Object | 与基督教家庭有联系 |
—
|
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: 与基督教家庭有联系 | Statement: [倪桂珍, 宗教背景, 与基督教家庭有联系]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 宗教背景 Context triple: [倪桂珍, 宗教背景, 与基督教家庭有联系]
-
A.
religiousEnvironment
chosen
Indicates the religious context, atmosphere, or setting in which an entity exists or an action takes place.
-
B.
religiousFoundation
Indicates that an entity was established, created, or founded by a religious organization, authority, or tradition.
-
C.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
D.
religiousCharacteristic
Indicates that one entity has a religious attribute, quality, or affiliation that characterizes or distinguishes it in a religious context.
-
E.
religiousCulturalContext
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72400911c8190978e88138a9bfaff |
completed | April 21, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:58 p.m.