Triple
T3547363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christianization of the Franks |
E75027
|
entity |
| Predicate | impactOnSociety |
P4312
|
FINISHED |
| Object | rise of episcopal power |
—
|
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: rise of episcopal power | Statement: [Christianization of the Franks, impactOnSociety, rise of episcopal power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnSociety Context triple: [Christianization of the Franks, impactOnSociety, rise of episcopal power]
-
A.
socialImpact
chosen
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
B.
impactOnHumans
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
C.
impactOnIndustry
Indicates the effect or influence that one entity, event, or action has on the state, performance, or development of an industry.
-
D.
impactOnLaw
Indicates the effect or influence that one entity, event, or action has on laws, legal rules, or the legal system.
-
E.
hasViewOnSociety
Indicates that an entity holds a particular perspective, opinion, or stance regarding society or social structures.
- 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbfd0eb6081908f1380db4cfade87 |
completed | March 8, 2026, 6:28 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:20 p.m.