Triple
T13825430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masonic degrees |
E332236
|
entity |
| Predicate | numberOfCoreDegrees |
P111654
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Masonic degrees, numberOfCoreDegrees, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoreDegrees Context triple: [Masonic degrees, numberOfCoreDegrees, 3]
-
A.
hasCoreDegrees
Indicates that an entity possesses one or more primary or foundational academic degrees.
-
B.
numberOfCoreAxioms
Indicates the specific count of fundamental axioms that form the core basis of a given system or theory.
-
C.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
-
D.
minimumDegree
Indicates that the relationship specifies the smallest number of connections or edges incident to any entity within a given structure or set.
-
E.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
- F. None of above. chosen
Provenance (4 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0285fb7c8190be4b90bdc0d6fa53 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:13 p.m.