Triple
T2114041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASN.1 |
E42565
|
entity |
| Predicate | hasEncodingRule |
P33682
|
FINISHED |
| Object | BER |
—
|
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: BER | Statement: [ASN.1, hasEncodingRule, BER]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEncodingRule Context triple: [ASN.1, hasEncodingRule, BER]
-
A.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
B.
encodedInUnicodeSince
Indicates that a given character or symbol has been included and assigned a code point in the Unicode standard starting from a specific version or time.
-
C.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
D.
encodedIn
Indicates that one entity is represented, stored, or expressed within another entity using a specific encoding or format.
-
E.
dataEncodingMethod
chosen
Indicates the specific technique or format used to encode data for storage, transmission, or processing.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb05b51c81908a78c816f492c45c |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.