Triple
T35550442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Cosmas and Damian in Kaluga |
E1027342
|
entity |
| Predicate | hasTwinPatronSaints |
P142740
|
FINISHED |
| Object | Cosmas and Damian |
—
|
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: Cosmas and Damian | Statement: [Church of Cosmas and Damian in Kaluga, hasTwinPatronSaints, Cosmas and Damian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwinPatronSaints Context triple: [Church of Cosmas and Damian in Kaluga, hasTwinPatronSaints, Cosmas and Damian]
-
A.
hasPatronSaint
Indicates that one entity serves as the patron saint associated with, protecting, or representing another entity.
-
B.
hasTwinTown
Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
-
C.
hasTwin
Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
-
D.
hasTwinCharacters
Indicates that two characters are twins, sharing the same parents and birth time or very close birth times.
-
E.
coPatronSaint
chosen
Indicates that two or more saints share the role of patronage over the same place, group, or cause.
- 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_69f76e014fd481909e9f04ac603a2aa9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.