Triple
T23197111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Failing |
E579900
|
entity |
| Predicate | belongsToWorkLanguage |
P45484
|
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: [Mrs. Failing, belongsToWorkLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToWorkLanguage Context triple: [Mrs. Failing, belongsToWorkLanguage, English]
-
A.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
B.
hasWorkedInLanguage
chosen
Indicates that an entity has performed work or professional activities using a particular language.
-
C.
workLanguageOfTitle
Indicates the language in which a specific work or title is expressed or written.
-
D.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
E.
hasOfficialLanguageOfWork
Indicates that an entity uses a specified language as its official medium for conducting work or formal activities.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fdc0b8081909242fdc5cb1da517 |
completed | April 29, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:06 p.m.