Triple
T20049086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 志忠 |
E499143
|
entity |
| Predicate | meaningComponent忠 |
P138511
|
FINISHED |
| Object | loyalty |
—
|
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: loyalty | Statement: [志忠, meaningComponent忠, loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningComponent忠 Context triple: [志忠, meaningComponent忠, loyalty]
-
A.
meaningComponent郎
Indicates that one entity is a semantic component or constituent part of the overall meaning of another entity.
-
B.
meaningComponent
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
meaningComponent樹
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
D.
meaningComponent_mar
Indicates that something is a semantic or conceptual component contributing to the overall meaning of another item, such as a word, phrase, or expression.
-
E.
hasMeaningInChinese
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning or interpretation within the Chinese language.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:37 p.m.