Triple
T27971630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wengong |
E706372
|
entity |
| Predicate | honorificMeaningCategory |
P20172
|
FINISHED |
| Object | meritorious service in civil affairs |
—
|
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: meritorious service in civil affairs | Statement: [Wengong, honorificMeaningCategory, meritorious service in civil affairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorificMeaningCategory Context triple: [Wengong, honorificMeaningCategory, meritorious service in civil affairs]
-
A.
honorificSense
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
B.
honorificType
chosen
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
C.
honorificConnotation
Indicates that one entity refers to or characterizes another using an honorific or respectful form, conveying deference or elevated social status.
-
D.
honorificIndicates
Indicates that one entity uses an honorific title or respectful form of address to refer to or address another entity.
-
E.
honorificMeaningOfName
Indicates that a name carries an honorific or respectful meaning associated with a person or entity.
- 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_69ef96b7f330819090f315318ba6977e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f676c440708190a4b9974e95d2291a |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 27, 2026, 7:38 p.m.