Triple
T31083853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPC-E |
E792173
|
entity |
| Predicate | encodingCharacterSet |
P8572
|
FINISHED |
| Object | UPC left-hand patterns only |
—
|
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: UPC left-hand patterns only | Statement: [UPC-E, encodingCharacterSet, UPC left-hand patterns only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encodingCharacterSet Context triple: [UPC-E, encodingCharacterSet, UPC left-hand patterns only]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
localEncoding
Indicates that an entity is represented or stored using a specific encoding scheme that is defined or applied locally within a particular context or system.
-
C.
codingSystemType
Indicates the classification or category of coding system used to encode or represent information in a given context.
-
D.
characterSetType
chosen
Indicates the type or category of character set associated with or used by an entity.
-
E.
encodingIndependence
Indicates that a relationship or property holds regardless of the specific encoding or representation used for the involved entities.
- 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_69f224ce48348190bd0fc23f656ed683 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:02 p.m.