Triple
T21112165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | interwar Republic of Estonia |
E520199
|
entity |
| Predicate | landReformEffect |
P100102
|
FINISHED |
| Object | expropriation of large estates |
—
|
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: expropriation of large estates | Statement: [interwar Republic of Estonia, landReformEffect, expropriation of large estates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landReformEffect Context triple: [interwar Republic of Estonia, landReformEffect, expropriation of large estates]
-
A.
effectOnPeasants
chosen
Indicates how an action, event, or condition impacts or influences peasants.
-
B.
hasLandownershipInfluenceOn
Indicates that one entity’s ownership or control of land affects, shapes, or exerts power over another entity or situation.
-
C.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
D.
landGrantField
Indicates that a specific field or parcel of land has been allocated or granted, typically by an authority, to a recipient under a land grant arrangement.
-
E.
economicTransition
Indicates a change in an entity’s economic system, structure, or status from one state or model to another.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72102d99c8190a1ea5a6981da6da0 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:54 p.m.