Triple
T2007430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EAN-13 barcode system |
E43616
|
entity |
| Predicate | readingTechnology |
P35106
|
FINISHED |
| Object | optical barcode scanner |
—
|
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: optical barcode scanner | Statement: [EAN-13 barcode system, readingTechnology, optical barcode scanner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingTechnology Context triple: [EAN-13 barcode system, readingTechnology, optical barcode scanner]
-
A.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
B.
readingExperience
Indicates the relationship in which an entity engages with written or visual material, capturing the act, manner, or quality of that reading activity.
-
C.
traditionalBooks
Indicates that the relationship or action involves conventional, physical print books as opposed to digital or alternative formats.
-
D.
libraryType
Indicates the specific category or classification of a library based on its function, scope, or organizational role.
-
E.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
- F. None of above. chosen
Provenance (4 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8999e108190a07daa01452a5dab |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.