Triple
T9326023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EAN-2 |
E224386
|
entity |
| Predicate | usesEncodingScheme |
P33682
|
FINISHED |
| Object | parity pattern based on modulo-4 of the two-digit value |
—
|
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: parity pattern based on modulo-4 of the two-digit value | Statement: [EAN-2, usesEncodingScheme, parity pattern based on modulo-4 of the two-digit value]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEncodingScheme Context triple: [EAN-2, usesEncodingScheme, parity pattern based on modulo-4 of the two-digit value]
-
A.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
B.
usesCodec
Indicates that one entity employs or relies on a specific codec to encode, decode, or process data.
-
C.
dataEncodingMethod
chosen
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
-
D.
usesEncryptionAlgorithm
Indicates that one entity applies or relies on a specific encryption algorithm to protect data or communications.
-
E.
notEncodedIn
Indicates that a piece of information, data, or content is explicitly absent from or not represented within a given encoding, format, or medium.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd36f88e988190bb896a3d7c3c723c |
completed | April 1, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:39 p.m.