Triple
T32594349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quang Hưng |
E833160
|
entity |
| Predicate | appliedToDocuments |
P147661
|
FINISHED |
| Object | royal edicts |
—
|
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: royal edicts | Statement: [Quang Hưng, appliedToDocuments, royal edicts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToDocuments Context triple: [Quang Hưng, appliedToDocuments, royal edicts]
-
A.
appliedInDocuments
chosen
Indicates that something (such as a method, rule, or concept) is used or implemented within one or more documents.
-
B.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
C.
documentedBy
Indicates that something is recorded, described, or evidenced in a specific document or set of documents.
-
D.
appliedToText
Indicates that something (such as a process, operation, or annotation) is performed on or associated with a specific piece of text.
-
E.
affectsDocument
Indicates that one entity produces an influence or change on a document, altering its state, content, or properties.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fed48d8e148190a99c0aea29f8a3ee |
completed | May 9, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fed3c82a24819095e614e31ac0307f |
completed | May 9, 2026, 6:27 a.m. |
Created at: May 1, 2026, 1:05 a.m.