Triple
T2535827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Defenestration of Prague (1618) |
E56265
|
entity |
| Predicate | hasWindowHeight |
P9788
|
FINISHED |
| Object | approximately 21 meters |
—
|
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: approximately 21 meters | Statement: [Defenestration of Prague (1618), hasWindowHeight, approximately 21 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWindowHeight Context triple: [Defenestration of Prague (1618), hasWindowHeight, approximately 21 meters]
-
A.
hasHeight
chosen
Indicates that one entity possesses a specific vertical measurement or stature.
-
B.
currentHeight
Indicates the present vertical measurement or elevation of an entity at a given point in time.
-
C.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
D.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
E.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
- 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_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. |
Created at: March 6, 2026, 9:47 p.m.