Triple
T20646002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sejo of Joseon |
E507356
|
entity |
| Predicate | legalWork |
P27701
|
FINISHED |
| Object | promotion of state law code compilation |
—
|
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: promotion of state law code compilation | Statement: [Sejo of Joseon, legalWork, promotion of state law code compilation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalWork Context triple: [Sejo of Joseon, legalWork, promotion of state law code compilation]
-
A.
legalPractice
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
-
B.
legalBackground
Indicates that an entity has education, training, or experience related to law or the legal profession.
-
C.
legalFormOfWork
Indicates the legally defined type or classification of employment or work arrangement under which an activity is performed.
-
D.
legalTextTypeWorkedOn
chosen
Indicates that an entity has worked on or handled a specific type or category of legal text.
-
E.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1dd79481909de985d03ab861c2 |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.