Triple
T28373580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yang Guifei |
E718696
|
entity |
| Predicate | oneOfFourBeauties |
P166874
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Yang Guifei, oneOfFourBeauties, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oneOfFourBeauties Context triple: [Yang Guifei, oneOfFourBeauties, Yes]
-
A.
eraOfPorcelain
Indicates the historical period or era during which a particular style or type of porcelain was produced or prominent.
-
B.
associatedEmpress
Indicates a relationship where an empress is linked or connected to another entity, such as a person, place, event, or object, in a relevant or context-specific way.
-
C.
eraAsEmpress
Indicates the time period during which a person held the role or status of empress.
-
D.
Xiaoerjing
Indicates a relationship where something is written, represented, or transcribed using the Xiaoerjing (Arabic-based) script for Sinitic languages.
-
E.
producedEmpress
Indicates that one entity created, generated, or brought about the existence or status of an empress.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f664aa283c8190a869d0555eff60c6 |
completed | May 2, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f6645a615481909b53d94512ecbaf1 |
completed | May 2, 2026, 8:53 p.m. |
Created at: April 28, 2026, 1:01 a.m.