Triple
T27323726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shang Xiaoyun |
E689580
|
entity |
| Predicate | performanceSpecialty |
P179471
|
FINISHED |
| Object | noble and dignified female characters |
—
|
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: noble and dignified female characters | Statement: [Shang Xiaoyun, performanceSpecialty, noble and dignified female characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performanceSpecialty Context triple: [Shang Xiaoyun, performanceSpecialty, noble and dignified female characters]
-
A.
performanceWith
Indicates a relationship where two or more entities participate together in the same performance or staged presentation.
-
B.
performanceAs
Indicates that one entity serves in a particular role, character, or capacity within a performance or presentation involving another entity.
-
C.
performanceIncludes
Indicates that a performance encompasses, contains, or is composed of a specified component, act, segment, or element.
-
D.
performanceDescribedAs
Indicates that a performance is characterized or labeled using a particular description or evaluative term.
-
E.
performanceClass
Indicates the category or level of performance to which an entity is assigned, typically reflecting its capabilities or quality tier.
- 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f722c1bc648190a79bfdc722dcaaa4 |
completed | May 3, 2026, 10:26 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f7221bc57c819085c1464a45e61b2f |
completed | May 3, 2026, 10:23 a.m. |
Created at: April 27, 2026, 11:34 a.m.