Triple
T3575387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dillard University (Theological training, informal/extension context) |
E75674
|
entity |
| Predicate | formalDegreeTrack |
P49798
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Dillard University (Theological training, informal/extension context), formalDegreeTrack, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formalDegreeTrack Context triple: [Dillard University (Theological training, informal/extension context), formalDegreeTrack, no]
-
A.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
B.
hasFormalStatus
Indicates that an entity possesses an officially recognized or legally defined status within a formal system or context.
-
C.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
D.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
E.
hasHighestRegularDegree
Indicates that the subject has the greatest regular (non-irregular or non-special) degree value among a set of comparable entities.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0da77008190922f414b85b9cad4 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb8e4ba948190a9b777cf7f788b96 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:21 p.m.