Triple
T25387485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yum-Yum |
E631563
|
entity |
| Predicate | spokenLanguageInWork |
P125070
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Yum-Yum, spokenLanguageInWork, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenLanguageInWork Context triple: [Yum-Yum, spokenLanguageInWork, English]
-
A.
languageWithinWork
chosen
Indicates that a specific language is used or contained within a particular work (such as a document, publication, or creative piece).
-
B.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
C.
lenguaDeTrabajo
Indicates that something functions as a working language used for communication in a specific context or setting.
-
D.
لغة_الأعمال
Indicates a relationship where something is expressed, conducted, or communicated using the language of business (لغة الأعمال).
-
E.
placeInWork
Indicates that one entity is located or occurs within the spatial or structural context of another entity in a work.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f5656c16ac8190be99d40cb63f9541 |
completed | May 2, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:47 p.m.