Triple
T8869887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Francis Sutton Jr. |
E211124
|
entity |
| Predicate | languageOfQuote |
P81876
|
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: [William Francis Sutton Jr., languageOfQuote, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfQuote Context triple: [William Francis Sutton Jr., languageOfQuote, English]
-
A.
quoteLanguage
chosen
Indicates that a quoted text is expressed in a particular language.
-
B.
notableQuoteTranslation
Indicates that one quote is a translation of another quote, preserving its meaning across different languages.
-
C.
languageOfHonoredFigure
Indicates the language associated with or used by the person who is being honored.
-
D.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
E.
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).
- 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61257a548190955ad71f4c8704d5 |
completed | April 1, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:51 p.m.