Triple
T6222967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurzweil reading machine for the blind |
E139158
|
entity |
| Predicate | readingMethod |
P37920
|
FINISHED |
| Object | scan-convert-speak pipeline |
—
|
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: scan-convert-speak pipeline | Statement: [Kurzweil reading machine for the blind, readingMethod, scan-convert-speak pipeline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingMethod Context triple: [Kurzweil reading machine for the blind, readingMethod, scan-convert-speak pipeline]
-
A.
readingApproach
chosen
Indicates the method, strategy, or manner in which an entity engages in reading a text.
-
B.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
C.
readsFrom
Indicates that one entity obtains or accesses data, information, or content from another entity as a source.
-
D.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
-
E.
readIn
Indicates that an entity reads or studies something within a particular location or context.
- 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_69c008aecb0c81909984b48f733ce8ae |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062c06c7881909999ba44aa4a23f9 |
completed | March 22, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69c055ffdf54819086d987d646e44ff5 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.