Triple
T859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mens et Manus |
E16
|
entity |
| Predicate | relatedConcept |
P37
|
FINISHED |
| Object | polytechnic 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: polytechnic education | Statement: [Mens et Manus, relatedConcept, polytechnic education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedConcept Context triple: [Mens et Manus, relatedConcept, polytechnic education]
-
A.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
introducedConcept
Indicates that one entity is responsible for presenting, defining, or bringing a new concept into use or awareness for another entity or context.
-
C.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
D.
complements
Indicates that one entity enhances, completes, or improves another by providing qualities or functions that fit well together.
-
E.
alsoKnownAs
Indicates that one entity is an alternative name, alias, or designation for another 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23344daf8819083118bbac5f46568 |
completed | Feb. 28, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69a232e52e7c81909c072703e28e8c61 |
completed | Feb. 28, 2026, 12:12 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.