Triple
T31463523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Sign Language |
E802664
|
entity |
| Predicate | hasInterpreters |
P86917
|
FINISHED |
| Object | professional LIS interpreters |
—
|
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: professional LIS interpreters | Statement: [Italian Sign Language, hasInterpreters, professional LIS interpreters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterpreters Context triple: [Italian Sign Language, hasInterpreters, professional LIS interpreters]
-
A.
useOfInterpreters
chosen
Indicates that interpreters are employed to facilitate communication between parties who do not share a common language or communication mode.
-
B.
hasInterpretiveElement
Indicates that something includes or is associated with an element involving interpretation, such as a subjective, analytical, or explanatory component.
-
C.
isInterpretedBy
Indicates that something (such as data, a work, or a signal) is given meaning, understanding, or explanation by a particular agent or process.
-
D.
hasBytecodeInterpreter
Indicates that an entity includes or uses a bytecode interpreter to execute bytecode instructions.
-
E.
isInterpretableIn
Indicates that one formal system, language, or theory can be meaningfully represented, understood, or given a semantics within another system, language, or theory.
- 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_69f348c84c1c81908739f100ecf7394e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff48199b1c8190bb05872f8a4f4673 |
completed | May 9, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69ff4746b1cc8190854f70a124df7d04 |
completed | May 9, 2026, 2:40 p.m. |
Created at: April 30, 2026, 9:21 p.m.