Triple
T15803358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lei |
E383148
|
entity |
| Predicate | hasMeaningWhenCharacterIs蕾 |
P59026
|
FINISHED |
| Object | bud |
—
|
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: bud | Statement: [Lei, hasMeaningWhenCharacterIs蕾, bud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningWhenCharacterIs蕾 Context triple: [Lei, hasMeaningWhenCharacterIs蕾, bud]
-
A.
hasLastThreeLettersMeaning
Indicates that the last three letters of one entity (typically a word or string) together form a meaningful unit or have a specific semantic significance.
-
B.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
C.
associatedCharacterMeaning
chosen
Indicates that there is a relationship between a character and the meaning, interpretation, or concept that this character is intended to represent.
-
D.
characterCorrespondsTo
Indicates that one character is equivalent to, maps onto, or represents another character in a defined correspondence or mapping.
-
E.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b524835c8190ae286b2562f07756 |
completed | April 16, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:48 a.m.