Triple
T29100157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | π/4 DQPSK |
E736616
|
entity |
| Predicate | typicalFilter |
P151371
|
FINISHED |
| Object | root raised cosine pulse shaping |
—
|
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: root raised cosine pulse shaping | Statement: [π/4 DQPSK, typicalFilter, root raised cosine pulse shaping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFilter Context triple: [π/4 DQPSK, typicalFilter, root raised cosine pulse shaping]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
C.
typicalGroup
Indicates that the subject belongs to or represents a standard, characteristic, or commonly occurring group associated with the object.
-
D.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
E.
typicalProperty
chosen
Indicates that a certain property is characteristically or commonly associated with an entity, reflecting what is typical for that entity.
- 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a0174142430819084aa1235500b9d3b |
completed | May 11, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_6a0171a6e0088190958679bb6cb24a70 |
completed | May 11, 2026, 6:05 a.m. |
Created at: April 28, 2026, 11:11 a.m.