Triple
T21927509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juris Doctor |
E541478
|
entity |
| Predicate | degreeFormat |
P146595
|
FINISHED |
| Object | coursework-based |
—
|
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: coursework-based | Statement: [Juris Doctor, degreeFormat, coursework-based]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeFormat Context triple: [Juris Doctor, degreeFormat, coursework-based]
-
A.
degreeForm
Indicates that one entity is the specific academic degree or qualification conferred in the context of another entity (such as a program, award, or credential).
-
B.
degreeOver
Indicates that one entity’s degree, level, or extent exceeds that of another entity.
-
C.
degreeNumber
Indicates the specific numeric value assigned to a degree, such as its level, rank, or sequence number.
-
D.
typicalTemperatureScale
Indicates the temperature scale (such as Celsius or Fahrenheit) that is normally used to express temperature values for the given entity or context.
-
E.
degreeIn2
Indicates that the second entity holds an academic degree in the field or program represented by the first 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_69e0c47d74488190a15119108794a307 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f123fc188481909c74fd5f1bd52258 |
completed | April 28, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb6991948190a428c3c3bfd1c3b8 |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:46 p.m.