Triple
T2535826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Defenestration of Prague (1618) |
E56265
|
entity |
| Predicate | hasNumberOfDefenestratedOfficials |
P40953
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Defenestration of Prague (1618), hasNumberOfDefenestratedOfficials, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfDefenestratedOfficials Context triple: [Defenestration of Prague (1618), hasNumberOfDefenestratedOfficials, 3]
-
A.
hasNumberOfMinisters
Indicates the specific count of ministers associated with an entity, such as a government, cabinet, or organization.
-
B.
overthrownIn
Indicates that one entity (such as a government, leader, or regime) was removed from power or defeated in a specific event, context, or time period represented by the other entity.
-
C.
hasNumberOfRulers
Indicates the quantity of rulers associated with or governing a given entity.
-
D.
hasChancellor
Indicates that an entity holds the position or role of chancellor for another entity.
-
E.
numberOfPeopleExecuted
Indicates the total count of individuals who were put to death, typically as a result of a formal execution process.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd648487881908ce8ca22def77294 |
completed | March 7, 2026, 7:39 a.m. |
Created at: March 6, 2026, 9:47 p.m.