Triple
T16584135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzhounese |
E402908
|
entity |
| Predicate | historicalPrestige |
P37289
|
FINISHED |
| Object | literary language of Suzhou kunqu opera |
—
|
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: literary language of Suzhou kunqu opera | Statement: [Suzhounese, historicalPrestige, literary language of Suzhou kunqu opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalPrestige Context triple: [Suzhounese, historicalPrestige, literary language of Suzhou kunqu opera]
-
A.
historicalPower
Indicates that one entity held significant influence, control, or authority over another during a past period.
-
B.
historicalNotability
chosen
Indicates that an entity is recognized as having significant importance, influence, or prominence in history.
-
C.
historicallyRich
Indicates that an entity possesses significant historical depth, importance, or a wealth of notable past events and heritage.
-
D.
historicalLevel
Indicates the degree or extent to which something is related to, situated in, or characterized by a particular historical period or context.
-
E.
historicalCategory
Indicates that an entity is classified within a particular historical grouping, period, or type based on its time-related characteristics or 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35999f80c8190852fd4137bc45a80 |
completed | April 18, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e296a7d9d0819088555bca6c936e79 |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:16 a.m.