Triple
T13819377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letter G (Masonic symbol) |
E332096
|
entity |
| Predicate | hasMeaningIn |
P29818
|
FINISHED |
| Object | English‑speaking Masonic jurisdictions |
—
|
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‑speaking Masonic jurisdictions | Statement: [Letter G (Masonic symbol), hasMeaningIn, English‑speaking Masonic jurisdictions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningIn Context triple: [Letter G (Masonic symbol), hasMeaningIn, English‑speaking Masonic jurisdictions]
-
A.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
B.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
C.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
-
D.
hasSense
chosen
Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
-
E.
hasMeaningInSanskrit
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Sanskrit language.
- 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.