Triple
T1292135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cluny Abbey |
E27569
|
entity |
| Predicate | patronageFrom |
P28165
|
FINISHED |
| Object | papacy |
—
|
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: papacy | Statement: [Cluny Abbey, patronageFrom, papacy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: patronageFrom Context triple: [Cluny Abbey, patronageFrom, papacy]
-
A.
patronage
Indicates a relationship where one party supports, sponsors, or protects another, often in exchange for loyalty, services, or influence.
-
B.
patronageArea
Indicates the geographic or administrative area within which a patron (such as a sponsor, supporter, or benefactor) exercises their support, influence, or protective role.
-
C.
countryOfPatronage
Indicates the country that officially supports, sponsors, or acts as a patron for a given entity or activity.
-
D.
architecturalPatron
Indicates a relationship where one entity commissions, supports, or sponsors the design or construction of architecture created by another entity.
-
E.
patronState
Indicates a relationship where one state acts as a protector, sponsor, or dominant supporter of another state or political entity.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d7d15081909d3af19b9297f1cc |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:51 p.m.