Triple
T14696807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hong |
E345182
|
entity |
| Predicate | canBeMultipleCharacters |
P59069
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hong, canBeMultipleCharacters, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeMultipleCharacters Context triple: [Hong, canBeMultipleCharacters, yes]
-
A.
canRepresentMultipleChineseCharacters
Indicates that a given form (such as a sound, syllable, or written unit) is capable of corresponding to more than one distinct Chinese character.
-
B.
canBeWrittenWithMultipleKanji
chosen
Indicates that the same word or expression can be represented using more than one distinct kanji spelling.
-
C.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
D.
hasMultiple
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
-
E.
providesAdditionalCharactersFor
Indicates that one entity supplies extra or supplementary characters to be used by another entity or process.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb58855e081908b38f9515db5677f |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.