Triple
T32135478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mezze |
E820753
|
entity |
| Predicate | courseRelation |
P173612
|
FINISHED |
| Object | can precede a main course |
—
|
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: can precede a main course | Statement: [Mezze, courseRelation, can precede a main course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseRelation Context triple: [Mezze, courseRelation, can precede a main course]
-
A.
associatedCourse
Indicates that one entity is linked or connected to a particular course in a relevant or contextual way.
-
B.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
C.
examRelationship
Indicates a relationship between an exam and another entity, such as who took it, administered it, or is otherwise associated with it.
-
D.
seriesRelation
Indicates a relationship where one entity is part of, follows from, or is otherwise connected to another within an ordered series or sequence.
-
E.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b9a9bc4c8190a88918fc4f91136a |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a970b0819090c6473844ffa8e3 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: May 1, 2026, 12:30 a.m.