Triple
T3058903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kresy |
E60547
|
entity |
| Predicate | timeOfAnnexation |
P9024
|
FINISHED |
| Object | 1939 |
—
|
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: 1939 | Statement: [Kresy, timeOfAnnexation, 1939]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfAnnexation Context triple: [Kresy, timeOfAnnexation, 1939]
-
A.
annexationDate
chosen
Indicates the date on which one entity formally annexed or incorporated another entity into its territory or jurisdiction.
-
B.
annexedInYear
Indicates that one entity was formally annexed or incorporated into another in the specified calendar year.
-
C.
annexedDuring
Indicates that one entity was formally incorporated into and brought under the control of another entity during a specified time period.
-
D.
wasAnnexedInPartition
Indicates that a territory or entity was incorporated into another as a result of a formal partition of land or political division.
-
E.
unificationDate
Indicates the date on which two or more previously separate entities were formally unified into a single entity.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e1741648190b710b7022252498d |
completed | March 8, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.