Triple
T33125065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book I |
E847698
|
entity |
| Predicate | workLanguageFeature |
P5192
|
FINISHED |
| Object | multilingual wordplay |
—
|
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: multilingual wordplay | Statement: [Book I, workLanguageFeature, multilingual wordplay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageFeature Context triple: [Book I, workLanguageFeature, multilingual wordplay]
-
A.
languageFeature
chosen
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
B.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
C.
usesLanguageSupport
Indicates that one entity makes use of language-related assistance, features, or services provided by another entity.
-
D.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
- 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d71f3d00819088efa93eac76e17b |
completed | May 3, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69f6d27224708190b31a541cebe0ff77 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:27 a.m.