Triple
T27871794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 熊氏 |
E704508
|
entity |
| Predicate | hasCommonLanguageVariant |
P195088
|
FINISHED |
| Object | Mandarin Chinese |
—
|
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: Mandarin Chinese | Statement: [熊氏, hasCommonLanguageVariant, Mandarin Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonLanguageVariant Context triple: [熊氏, hasCommonLanguageVariant, Mandarin Chinese]
-
A.
hasCommonTranslationLanguage
Indicates that two entities share at least one language into which both can be or have been translated.
-
B.
isTranslationVariantOf
Indicates that one expression is a different linguistic rendering or version of the same content as another expression, typically across languages or translation forms.
-
C.
hasNameVariantLanguage
chosen
Indicates that a name variant is associated with or expressed in a specific language.
-
D.
languageVariants
Indicates that one language form is a variant or alternative version of another language.
-
E.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
- 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff519b65f081909902ba83b775ef85 |
completed | May 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69ff506fccdc8190bd93269589040aed |
completed | May 9, 2026, 3:19 p.m. |
Created at: April 27, 2026, 6:24 p.m.