Triple
T12310681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Ingolstadt |
E293468
|
entity |
| Predicate | opposingSideReligion |
P11272
|
FINISHED |
| Object | Protestant |
—
|
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: Protestant | Statement: [Battle of Ingolstadt, opposingSideReligion, Protestant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposingSideReligion Context triple: [Battle of Ingolstadt, opposingSideReligion, Protestant]
-
A.
primaryOpponentsReligion
Indicates the religion or belief system followed by an entity’s main or primary opponent.
-
B.
religiousSide
Indicates that one entity is aligned with, belongs to, or represents a particular religious faction, denomination, or side in a religious context.
-
C.
otherMajorReligion
Indicates that an entity’s primary religious affiliation is a major religion other than the one currently in focus or being referenced.
-
D.
otherReligion
chosen
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
E.
ethnicReligion
Indicates that a religion is closely associated with a particular ethnic group, often tied to that group’s culture, ancestry, or identity.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.