Triple
T7410900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Varieties of Religious Experience |
E170998
|
entity |
| Predicate | lectureYears |
P76777
|
FINISHED |
| Object | 1901 |
—
|
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: 1901 | Statement: [The Varieties of Religious Experience, lectureYears, 1901]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lectureYears Context triple: [The Varieties of Religious Experience, lectureYears, 1901]
-
A.
teachesFromYear
Indicates the year from which an entity (such as a person or institution) began teaching in a particular role, subject, or place.
-
B.
schoolYear
Indicates the academic year or grade level in which an entity (typically a student or class) is situated within an educational system.
-
C.
matriculationYear
Indicates the calendar year in which an individual formally enrolled or was admitted into an educational program or institution.
-
D.
academicYearType
Indicates the classification of an academic year according to its structural or administrative type (e.g., semester-based, quarter-based, fiscal year, etc.).
-
E.
hasSchoolYears
Indicates a relationship where an educational institution is associated with specific academic years or grade levels it offers or covers.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f29ebea48190be96c6bc1e6406fb |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.