Triple
T29112646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stefan Uroš V |
E736953
|
entity |
| Predicate | saintTitle |
P78467
|
FINISHED |
| Object | Saint Uroš |
—
|
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 Uroš | Statement: [Stefan Uroš V, saintTitle, Saint Uroš]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: saintTitle Context triple: [Stefan Uroš V, saintTitle, Saint Uroš]
-
A.
honorsTitleOfSaint
Indicates that an entity recognizes or bestows the formal religious title of "saint" upon another entity.
-
B.
saintName
chosen
Indicates that an entity has the specified name under which they are recognized or venerated as a saint.
-
C.
religiousTitle
Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
-
D.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
E.
traditionalMarianTitle
Indicates that the subject is referred to by a traditional honorific or devotional title associated with the Virgin Mary.
- 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f661ed89f08190a52d68a08a0be6bb |
completed | May 2, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:19 a.m.