Triple
T31942926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kwannon |
E815573
|
entity |
| Predicate | equivalentInChinese |
P28329
|
FINISHED |
| Object | Guanyin |
—
|
NE NERFINISHED |
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: Guanyin | Statement: [Kwannon, equivalentInChinese, Guanyin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentInChinese Context triple: [Kwannon, equivalentInChinese, Guanyin]
-
A.
hasMeaningInChinese
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning or interpretation within the Chinese language.
-
B.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
C.
languageEquivalent
chosen
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
equivalentInJapaneseKanji
Indicates that one entity has the same meaning or value as another entity when written in Japanese Kanji.
-
E.
equivalentEnglishForm
Indicates that two expressions share the same meaning in English, serving as equivalent linguistic forms.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 12:06 a.m.