Triple
T31252004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brace Up! |
E796848
|
entity |
| Predicate | workLanguageOfAdaptation |
P121206
|
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: [Brace Up!, workLanguageOfAdaptation, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageOfAdaptation Context triple: [Brace Up!, workLanguageOfAdaptation, English]
-
A.
workLanguageOfTitle
Indicates the language in which a specific work or title is expressed or written.
-
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.
adaptedInLanguage
chosen
Indicates that a work or content has been modified or translated so it can be presented or understood in a specified language.
-
D.
lenguaDeTrabajo
Indicates that something functions as a working language used for communication in a specific context or setting.
-
E.
languageOfMostAdaptations
Indicates the language in which the greatest number of adaptations of a given work or entity have been produced.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:11 p.m.