Triple
T852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mens et Manus |
E16
|
entity |
| Predicate | theme |
P261
|
FINISHED |
| Object | practical education |
—
|
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: practical education | Statement: [Mens et Manus, theme, practical education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theme Context triple: [Mens et Manus, theme, practical education]
-
A.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
B.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
C.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
D.
mission
Indicates that an entity is assigned or engaged in a specific task, operation, or purpose-directed undertaking.
-
E.
context
Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a23211181c81909c2db8796d2aded4 |
completed | Feb. 28, 2026, 12:08 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.