Triple
T31464478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senegalese Sign Language |
E802685
|
entity |
| Predicate | hasAcquisitionContext |
P48594
|
FINISHED |
| Object | Deaf schools in Senegal |
—
|
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: Deaf schools in Senegal | Statement: [Senegalese Sign Language, hasAcquisitionContext, Deaf schools in Senegal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcquisitionContext Context triple: [Senegalese Sign Language, hasAcquisitionContext, Deaf schools in Senegal]
-
A.
acquisitionContext
chosen
Indicates the circumstances, conditions, or setting under which an acquisition or purchase takes place.
-
B.
hasAcquisition
Indicates that one entity has acquired ownership or control of another entity, typically through a purchase or merger transaction.
-
C.
hasAcquisitionType
Indicates the specific kind or category of acquisition relationship that exists between one entity acquiring another.
-
D.
hasOperatingContext
Indicates the situational, environmental, or functional conditions under which an entity operates or is intended to be used.
-
E.
usesAcquisitionModel
Indicates that one entity employs or applies a particular acquisition model as the method or framework for obtaining something.
- 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_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 30, 2026, 9:22 p.m.