Triple
T3661047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tianqi Emperor |
E77647
|
entity |
| Predicate | courtCorruptionLevel |
P50219
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Tianqi Emperor, courtCorruptionLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtCorruptionLevel Context triple: [Tianqi Emperor, courtCorruptionLevel, high]
-
A.
courtOfficial
Indicates that an entity serves in an official capacity within a court, holding an authorized role in judicial or legal proceedings.
-
B.
affectedCourt
Indicates that a particular court is impacted or influenced by a specified action, decision, or legal matter.
-
C.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
D.
courtReported
Indicates that a court’s decision, proceedings, or judgment have been formally documented and made publicly available in a report or record.
-
E.
numberOfIndictedPersonsApproximate
Indicates an approximate count of persons who have been formally indicted in a given context or case.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d6fa188190a6db5bdae7083573 |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:25 p.m.