Triple
T31176343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Modestinus |
E794759
|
entity |
| Predicate | hasCompanionSaint |
P203716
|
FINISHED |
| Object | Saint Florentinus |
E553335
|
NE 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: Saint Florentinus | Statement: [Saint Modestinus, hasCompanionSaint, Saint Florentinus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompanionSaint Context triple: [Saint Modestinus, hasCompanionSaint, Saint Florentinus]
-
A.
hasMagicCompanion
Indicates that an entity is accompanied by or associated with another entity that serves as its magical companion.
-
B.
hasNumberOfCompanions
Indicates the quantity of companions or associates that an entity has.
-
C.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing another entity.
-
D.
hasCompanionPiece
Indicates that one item is conceptually or functionally paired with another item as its companion piece.
-
E.
hasCompanionCharacterProfession
Indicates that a companion character is associated with or practices a particular profession.
- F. None of above. chosen
Provenance (5 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01d077dcec8190b05b24b5de313b15 |
completed | May 11, 2026, 12:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a296bd10b18819094a353db891b31cb |
completed | June 10, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_6a01cea0e37881909cb6888518c6d12f |
completed | May 11, 2026, 12:42 p.m. |
| PDg | Predicate description generation | batch_6a01d0771fb88190809ac7ba18fb6565 |
completed | May 11, 2026, 12:49 p.m. |
Created at: April 29, 2026, 9:08 p.m.