Triple
T9666135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fanny Brawne |
E233708
|
entity |
| Predicate | lettersLanguage |
P38301
|
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: [Fanny Brawne, lettersLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lettersLanguage Context triple: [Fanny Brawne, lettersLanguage, English]
-
A.
languageOfLetters
chosen
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
B.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
C.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
D.
languageNote
Indicates a note or comment providing additional information or clarification about the language used or associated with an entity or resource.
-
E.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
- 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_69ca848d3b6c8190ae98ea554dea58df |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c38f65c8190a0ed20830249a0f1 |
completed | April 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b3239c8190b3ae3b9bd121e4bd |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:14 p.m.