Triple
T20646396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pabna agrarian disturbances of 1873–1876 |
E507365
|
entity |
| Predicate | mainTypeOfActor |
P53708
|
FINISHED |
| Object | peasants |
—
|
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: peasants | Statement: [Pabna agrarian disturbances of 1873–1876, mainTypeOfActor, peasants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTypeOfActor Context triple: [Pabna agrarian disturbances of 1873–1876, mainTypeOfActor, peasants]
-
A.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
B.
hasMainRole
Indicates that an entity holds the primary or most significant role in relation to another entity or context.
-
C.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
D.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
E.
actorRole
chosen
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1eee9c81908fd3b4fe8c4529c8 |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.