Triple
T29409614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiang Wei |
E745857
|
entity |
| Predicate | originallyServedState |
P200593
|
FINISHED |
| Object | Cao Wei |
—
|
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: Cao Wei | Statement: [Jiang Wei, originallyServedState, Cao Wei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallyServedState Context triple: [Jiang Wei, originallyServedState, Cao Wei]
-
A.
primaryOriginState
Indicates the state that serves as the main or original source location associated with an entity.
-
B.
originallyServes
Indicates that an entity was initially intended or designated to serve, function for, or be used by another entity or purpose.
-
C.
servedProvince
Indicates that an entity has provided services or held jurisdictional authority over a specified province.
-
D.
primaryStatesServed
Indicates the main geographic states that are principally served or covered by the subject.
-
E.
servesPartOfState
Indicates that an entity serves as an official or functional part of a larger state-level governmental or administrative structure.
- F. None of above. chosen
Provenance (4 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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69ff9a25407c81909faa86e72a7a9d17 |
completed | May 9, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69ff99c613688190a03b2f93d5ccad2b |
completed | May 9, 2026, 8:32 p.m. |
| PDg | Predicate description generation | batch_69ff9a24996c8190ba2c5345d317cbdb |
completed | May 9, 2026, 8:33 p.m. |
Created at: April 28, 2026, 2:56 p.m.