Triple
T19796587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melody Bledsoe |
E475557
|
entity |
| Predicate | communicatesPrimarilyIn |
P83252
|
FINISHED |
| Object | sign language |
—
|
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: sign language | Statement: [Melody Bledsoe, communicatesPrimarilyIn, sign language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: communicatesPrimarilyIn Context triple: [Melody Bledsoe, communicatesPrimarilyIn, sign language]
-
A.
spokenPrimarilyOn
Indicates that something (typically a language or dialect) is used mainly for spoken communication in a particular context, region, or group.
-
B.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
C.
primaryLanguageIn
Indicates that a specified language is the main or official language used within a particular place, organization, or context.
-
D.
hasPrimaryLanguage1
chosen
Indicates that an entity’s main or most commonly used language is the specified language.
-
E.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c723548190ac9bfaecaf8afb13 |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.