Triple
T1384043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Greece |
E29802
|
entity |
| Predicate | restoredMonarchy |
P27221
|
FINISHED |
| Object | 1935 |
—
|
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: 1935 | Statement: [Kingdom of Greece, restoredMonarchy, 1935]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restoredMonarchy Context triple: [Kingdom of Greece, restoredMonarchy, 1935]
-
A.
monarchyAbolishedIn
Indicates that a monarchy was officially ended or abolished in a specified place or at a specified time.
-
B.
monarchy
Indicates a system of governance in which supreme authority is vested in a single ruler, typically a king or queen, whose position is usually hereditary.
-
C.
secondMonarch
Indicates that one entity is the second monarch (in chronological order of reign) in relation to another specified realm, dynasty, or succession context.
-
D.
successorAsEmpressOfTheFrench
Indicates that one person became the next Empress of the French following another person in that imperial role.
-
E.
predecessorAsEmpressOfTheFrench
Indicates that one person previously held the title Empress of the French before another person, in a direct succession.
- F. None of above. chosen
Provenance (4 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3377b608190b915e6871c1fe86e |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.