Triple
T318176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavaria |
E7752
|
entity |
| Predicate | joinedFederalRepublicIn |
P1138
|
FINISHED |
| Object | 1949 |
—
|
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: 1949 | Statement: [Bavaria, joinedFederalRepublicIn, 1949]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: joinedFederalRepublicIn Context triple: [Bavaria, joinedFederalRepublicIn, 1949]
-
A.
numberOfUnionRepublicsAtDissolution
Indicates the total count of union republics that existed in a state at the time of its dissolution.
-
B.
countryJoined
chosen
Indicates that a country became a member of, or formally entered into, a specific organization, union, alliance, or agreement.
-
C.
unificationDate
Indicates the date on which two or more previously separate entities were formally unified into a single entity.
-
D.
associatedConfederationCount
Indicates the number of distinct confederations with which an entity is associated.
-
E.
wasUnifiedWith
Indicates that two or more previously separate entities were brought together to form a single unified whole.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.