Triple
T27968516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Chinese Odyssey |
E704790
|
entity |
| Predicate | memorableQuoteLanguage |
P81876
|
FINISHED |
| Object | Cantonese |
—
|
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: Cantonese | Statement: [A Chinese Odyssey, memorableQuoteLanguage, Cantonese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorableQuoteLanguage Context triple: [A Chinese Odyssey, memorableQuoteLanguage, Cantonese]
-
A.
quoteLanguage
chosen
Indicates that a quoted text is expressed in a particular language.
-
B.
notableQuoteTranslation
Indicates that one quote is a translation of another quote, preserving its meaning across different languages.
-
C.
memorableQuoteContext
Indicates the situational or narrative context in which a particular memorable quote was spoken or written.
-
D.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
E.
quotationText
Indicates that the associated text is the exact content of a quotation made or referenced in the relationship.
- 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 7:36 p.m.