Triple
T35081083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisteria Lane |
E1012436
|
entity |
| Predicate | languageOfOriginalWorkContext |
P21977
|
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: [Wisteria Lane, languageOfOriginalWorkContext, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOriginalWorkContext Context triple: [Wisteria Lane, languageOfOriginalWorkContext, English]
-
A.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
-
B.
workInOriginalLanguage
Indicates that a work is being created, presented, or studied in the language in which it was originally produced, without translation.
-
C.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
D.
originalLanguageContext
chosen
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
E.
originalLanguageText
Indicates that a text is expressed in its original, untranslated 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_69f76dd32c008190853aef6028f60208 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00ada2903481908b28ce55ef97a6c2 |
completed | May 10, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_6a00ad5d23788190b3f9e2de761d39bb |
completed | May 10, 2026, 4:07 p.m. |
Created at: May 3, 2026, 4:01 p.m.