Triple
T11004967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World English |
E260092
|
entity |
| Predicate | notationScope |
P61710
|
FINISHED |
| Object | sounds of standard spoken English |
—
|
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: sounds of standard spoken English | Statement: [World English, notationScope, sounds of standard spoken English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notationScope Context triple: [World English, notationScope, sounds of standard spoken English]
-
A.
notationDomain
Indicates a relationship where a notation system is associated with, or defined over, a particular domain in which it is valid or applicable.
-
B.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
C.
notationPurpose
Indicates that one notation is used with the specific purpose or function of representing, explaining, or supporting another entity or concept.
-
D.
scopeOfReference
chosen
Indicates the range or domain of things, concepts, or entities to which a reference, statement, or expression applies.
-
E.
encodingScope
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797562de4819097a0e136180d283a |
completed | April 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d72e96be6c8190a46c69f61b2d8cd4 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.