Triple
T30119604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaochengren |
E765521
|
entity |
| Predicate | childTitleOfYunreng |
P60911
|
FINISHED |
| Object | Crown Prince |
—
|
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: Crown Prince | Statement: [Empress Xiaochengren, childTitleOfYunreng, Crown Prince]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childTitleOfYunreng Context triple: [Empress Xiaochengren, childTitleOfYunreng, Crown Prince]
-
A.
childTitle
chosen
Indicates that one entity holds the title or designation of a child in relation to another entity.
-
B.
Xiaoerjing
Indicates a relationship where something is written, represented, or transcribed using the Xiaoerjing (Arabic-based) script for Sinitic languages.
-
C.
childName
Indicates that one entity is the name (or given name) of a child associated with another entity.
-
D.
childCharacter
Indicates that one entity is a child version or child role of another character entity.
-
E.
childInMyth
Indicates that one entity is described or portrayed as the child (offspring) of another entity within a mythological or legendary context.
- 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 7:13 p.m.