Triple
T12633920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summa |
E301709
|
entity |
| Predicate | genreComparedTo |
P7993
|
FINISHED |
| Object | medieval legal summae |
—
|
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: medieval legal summae | Statement: [Summa, genreComparedTo, medieval legal summae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreComparedTo Context triple: [Summa, genreComparedTo, medieval legal summae]
-
A.
genreContrast
chosen
Indicates a relationship where two or more works are compared or juxtaposed based on differences between their genres.
-
B.
genreDiversity
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
C.
usedGenre
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
D.
genreIncludes
Indicates that a broader genre category encompasses or contains a specified subgenre or work as part of its classification.
-
E.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:15 p.m.