Triple
T36215062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yin Yu |
E1047667
|
entity |
| Predicate | hasPrimaryNameLanguage |
P193771
|
FINISHED |
| Object | Chinese name "Yin Yu" |
—
|
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: Chinese name "Yin Yu" | Statement: [Yin Yu, hasPrimaryNameLanguage, Chinese name "Yin Yu"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryNameLanguage Context triple: [Yin Yu, hasPrimaryNameLanguage, Chinese name "Yin Yu"]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
hasPrimaryLanguageForToponym
chosen
Indicates that a particular language is the main or official language used for the naming or labeling of a specific place name (toponym).
-
C.
hasPrimaryVernacularLanguageFamily
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
D.
hasPrimaryTraditionalLanguage
Indicates that one entity is the main or principal traditional language associated with another entity.
-
E.
hasPrimaryEthnonym
Indicates that an entity is associated with its main or most commonly used ethnonym (ethnic group name) as its primary designation.
- 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_69f76e4214748190a76c986d2a1838c2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.