Triple
T10894395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Against the Panthers: A Study of Repression in America |
E257268
|
entity |
| Predicate | hasAuthorAcademicDegreeContext |
P96270
|
FINISHED |
| Object | PhD dissertation |
—
|
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: PhD dissertation | Statement: [War Against the Panthers: A Study of Repression in America, hasAuthorAcademicDegreeContext, PhD dissertation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorAcademicDegreeContext Context triple: [War Against the Panthers: A Study of Repression in America, hasAuthorAcademicDegreeContext, PhD dissertation]
-
A.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
B.
hasAcademicCharacter
Indicates that something possesses qualities, standards, or attributes associated with academic or scholarly work.
-
C.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
D.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
E.
hasAcademicRank
Indicates that an entity holds a specific academic rank or title within an educational or research institution.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75d0153408190bcba2d9b03d78804 |
completed | April 9, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69d70d3943c881908895397eccc3e415 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101de31c819090707635f6790559 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:21 p.m.