Triple
T20603323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliet’s Balcony |
E506237
|
entity |
| Predicate | hasLanguageOfAssociatedWork |
P34465
|
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: [Juliet’s Balcony, hasLanguageOfAssociatedWork, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfAssociatedWork Context triple: [Juliet’s Balcony, hasLanguageOfAssociatedWork, English]
-
A.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
B.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
-
C.
languageOfParentWork
chosen
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
D.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
E.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
- 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa22663881909a8d4644e1c48dc2 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.