Triple
T12245089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Jewish Cemetery in Prague |
E291829
|
entity |
| Predicate | burialsEstimated |
P14555
|
FINISHED |
| Object | up to 100000 |
—
|
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: up to 100000 | Statement: [Old Jewish Cemetery in Prague, burialsEstimated, up to 100000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: burialsEstimated Context triple: [Old Jewish Cemetery in Prague, burialsEstimated, up to 100000]
-
A.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
B.
burialsUntil
Indicates the number of burial events that remain or are scheduled to occur up to a specified point in time or condition.
-
C.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
D.
periodOfBurial
Indicates the time period or date range during which the burial of an entity took place.
-
E.
burials
Indicates that one entity is interred or laid to rest in a grave or burial site associated with another 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d38ee10819093ed41d2954bf4ef |
completed | April 10, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69d91c46dcd88190a263db30804bff36 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.