Triple
T12357967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Egon Spengler |
E294658
|
entity |
| Predicate | hasPhDIn |
P27881
|
FINISHED |
| Object | parapsychology |
—
|
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: parapsychology | Statement: [Dr. Egon Spengler, hasPhDIn, parapsychology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhDIn Context triple: [Dr. Egon Spengler, hasPhDIn, parapsychology]
-
A.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
B.
hasDoctoralSchool
Indicates that an individual or academic entity is affiliated with or obtained their doctoral education from a specific doctoral school or graduate institution.
-
C.
hasDoctoralProgram
Indicates that an institution or academic unit offers and administers a doctoral-level degree program.
-
D.
hasAcademicBackgroundIn
chosen
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
E.
hasDoctoralStudentsThrough
Indicates that one entity has doctoral students indirectly through another entity, such as via co-supervision, program affiliation, or intermediary supervision relationships.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.