Triple
T30206841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whatever Will Be, Will Be |
E767946
|
entity |
| Predicate | hasAssociatedLanguagePhrase |
P2303
|
FINISHED |
| Object | Que sera, sera |
—
|
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: Que sera, sera | Statement: [Whatever Will Be, Will Be, hasAssociatedLanguagePhrase, Que sera, sera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedLanguagePhrase Context triple: [Whatever Will Be, Will Be, hasAssociatedLanguagePhrase, Que sera, sera]
-
A.
hasAssociatedLanguagePair
Indicates a relationship where a resource or entity is linked to a specific pair of languages, typically denoting a source and target language used together.
-
B.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
-
C.
hasTermLanguage
Indicates that a given term is expressed or defined in a particular language.
-
D.
basedOnLanguagePhrase
Indicates that something is derived from, informed by, or constructed using a specific phrase in a particular natural language.
-
E.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 29, 2026, 7:31 p.m.