Triple
T29027780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leben und Tod der heiligen Genoveva |
E737640
|
entity |
| Predicate | hasSaintSubject |
P494
|
FINISHED |
| Object | Saint Genevieve |
—
|
NE NERFINISHED |
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 Genevieve | Statement: [Leben und Tod der heiligen Genoveva, hasSaintSubject, Saint Genevieve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSaintSubject Context triple: [Leben und Tod der heiligen Genoveva, hasSaintSubject, Saint Genevieve]
-
A.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
-
B.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing another entity.
-
C.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
D.
hasSubjectPlace
Indicates that something is associated with or occurs in a particular subject-related place or location.
-
E.
hasNotableSubject
chosen
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 28, 2026, 9:53 a.m.