Triple
T13687943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caterina Sforza |
E328181
|
entity |
| Predicate | laterReleasedThrough |
P111171
|
FINISHED |
| Object | intervention of the French king Louis XII |
—
|
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: intervention of the French king Louis XII | Statement: [Caterina Sforza, laterReleasedThrough, intervention of the French king Louis XII]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterReleasedThrough Context triple: [Caterina Sforza, laterReleasedThrough, intervention of the French king Louis XII]
-
A.
laterReleased
Indicates that one entity was released at a time chronologically after the release of another entity.
-
B.
laterReleasedBy
Indicates that one entity was released at a later time than another entity by the same releasing agent or source.
-
C.
laterReleaseYear
Indicates that the release year of one entity occurs after the release year of another entity.
-
D.
releasedThrough
Indicates that something (such as a work, product, or content) is made publicly available or distributed via a particular channel, platform, or intermediary.
-
E.
alsoReleasedOn
Indicates that the same item (such as a work, product, or release) was made available on an additional platform, format, or medium besides its primary one.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc670968881908e2b4fdf656c7285 |
completed | April 12, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:53 p.m.