Triple
T26323893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Đinh Phế Đế |
E662191
|
entity |
| Predicate | scriptUsedInCourt |
P104647
|
FINISHED |
| Object | classical Chinese |
—
|
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: classical Chinese | Statement: [Đinh Phế Đế, scriptUsedInCourt, classical Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptUsedInCourt Context triple: [Đinh Phế Đế, scriptUsedInCourt, classical Chinese]
-
A.
scriptUsedForProceedings
chosen
Indicates that a particular writing system or script is used to record, document, or conduct the referenced proceedings.
-
B.
usedInCourts
Indicates that something is employed or applied within legal court settings, such as in judicial proceedings or courtroom processes.
-
C.
usedByCourt
Indicates that something (such as a document, argument, or evidence) is utilized or relied upon by a court in its judicial process.
-
D.
scriptInLaw
Indicates that a particular writing system or script is used within the text of a legal document or law.
-
E.
usedCourt
Indicates that an entity made use of or participated in legal proceedings within a particular court.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 26, 2026, 10:29 p.m.