Triple
T20005916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Child of Deaf Adults |
E494460
|
entity |
| Predicate | typicalBilingualStatus |
P103278
|
FINISHED |
| Object | bilingual in sign and spoken languages |
—
|
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: bilingual in sign and spoken languages | Statement: [Child of Deaf Adults, typicalBilingualStatus, bilingual in sign and spoken languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBilingualStatus Context triple: [Child of Deaf Adults, typicalBilingualStatus, bilingual in sign and spoken languages]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
C.
majorityBilingualWith
Indicates that the majority of individuals in a given group or population are bilingual in the two specified languages or language groups.
-
D.
usesBilingualInstruction
Indicates that an entity employs two languages as the medium of instruction within an educational or communicative context.
-
E.
bilingualismWith
chosen
Indicates a relationship where an entity possesses or is associated with the ability to use two specified languages.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a57ef881909115c8aa232b1012 |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:33 p.m.