Triple
T6743146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilhelm Meyer-Lübke |
E154137
|
entity |
| Predicate | dateOfDoctoralDegree |
P66963
|
FINISHED |
| Object | 1884 |
—
|
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: 1884 | Statement: [Wilhelm Meyer-Lübke, dateOfDoctoralDegree, 1884]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateOfDoctoralDegree Context triple: [Wilhelm Meyer-Lübke, dateOfDoctoralDegree, 1884]
-
A.
doctoralDegreeYear
chosen
Indicates the calendar year in which an entity received or completed their doctoral degree.
-
B.
degreeGrantedBy
Indicates that a specific academic degree was officially conferred by a particular granting institution.
-
C.
doctoralThesisPublicationYear
Indicates the year in which a person's doctoral thesis was formally published.
-
D.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
E.
conferredOn
Indicates that something (such as an honor, title, degree, or benefit) has been formally granted or bestowed upon a particular entity.
- 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_69c6880d84d8819095d19de2295f26ac |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b3b1448190a94b4b64f01af14a |
completed | March 27, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:10 p.m.