Triple
T3551865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hongzhi Emperor |
E75127
|
entity |
| Predicate | courtStyle |
P50550
|
FINISHED |
| Object | frugality |
—
|
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: frugality | Statement: [Hongzhi Emperor, courtStyle, frugality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtStyle Context triple: [Hongzhi Emperor, courtStyle, frugality]
-
A.
courtContext
Indicates the legal or judicial setting, circumstances, or framework within which a court-related action or relationship takes place.
-
B.
trialCourt
Indicates that a legal matter, decision, or proceeding is associated with, handled by, or occurring in a court of first instance (the trial-level court).
-
C.
courtLanguage
Indicates the language officially used in legal proceedings or by a court.
-
D.
hasTypeOfCourt
Indicates that an entity is associated with or classified by a specific type or category of court.
-
E.
courtCulture
Indicates the prevailing norms, practices, and behavioral expectations that characterize how a particular court operates and conducts its proceedings.
- 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc05256f081908b8d6a5df917e679 |
completed | March 8, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adba25c66c81909a05a97327828c41 |
completed | March 8, 2026, 6:04 p.m. |
Created at: March 8, 2026, 3:20 p.m.