Triple
T13819400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letter G (Masonic symbol) |
E332096
|
entity |
| Predicate | hasLanguageDependence |
P33278
|
FINISHED |
| Object | English alphabet |
—
|
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: English alphabet | Statement: [Letter G (Masonic symbol), hasLanguageDependence, English alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageDependence Context triple: [Letter G (Masonic symbol), hasLanguageDependence, English alphabet]
-
A.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
B.
hasDependency
Indicates that one entity relies on or requires another entity in order to function, exist, or be fulfilled.
-
C.
hasLanguageIndependentName
Indicates that an entity possesses a name or label that is the same across all languages, not tied to any specific linguistic form.
-
D.
isLanguageIndependent
chosen
Indicates that the relationship, property, or behavior holds true regardless of the specific natural language used to express or encode it.
-
E.
usesLanguageRuntime
Indicates that an entity operates using, depends on, or is executed within a specific language runtime environment.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0282d4d08190b754cda7683408c4 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.