Triple
T10227921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papal bull of Pope Clement VII |
E243253
|
entity |
| Predicate | hasTypeOfEffect |
P92873
|
FINISHED |
| Object | recognition of sovereignty |
—
|
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: recognition of sovereignty | Statement: [Papal bull of Pope Clement VII, hasTypeOfEffect, recognition of sovereignty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfEffect Context triple: [Papal bull of Pope Clement VII, hasTypeOfEffect, recognition of sovereignty]
-
A.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
B.
isQuantumEffect
Indicates that the relationship or phenomenon arises specifically from quantum mechanical principles or effects rather than classical behavior.
-
C.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
-
D.
hasEffectNamedAfter
Indicates that an entity has an effect or phenomenon that is named after another entity.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d23a9c4c8190abece9e52879c479 |
completed | April 7, 2026, 9:45 a.m. |
Created at: April 6, 2026, 11:18 a.m.