Triple
T30888933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandarmokh |
E786843
|
entity |
| Predicate | numberOfBurialsEstimate |
P14555
|
FINISHED |
| Object | over 7,000 |
—
|
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: over 7,000 | Statement: [Sandarmokh, numberOfBurialsEstimate, over 7,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBurialsEstimate Context triple: [Sandarmokh, numberOfBurialsEstimate, over 7,000]
-
A.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
B.
numberOfGravesApproximate
Indicates that the stated count of graves is an estimated or approximate number rather than an exact figure.
-
C.
numberOfInterred
Indicates the total count of individuals who are buried or interred at a given site or within a specified context.
-
D.
numberOfUnidentifiedBurials
Indicates the count of burial sites or graves where the interred individuals have not been identified.
-
E.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
- 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00b2b425a8819091ff65695e98c3af |
completed | May 10, 2026, 4:30 p.m. |
| PD | Predicate disambiguation | batch_6a00b06efa248190b2d16b4889185119 |
completed | May 10, 2026, 4:21 p.m. |
Created at: April 29, 2026, 8:49 p.m.