Triple
T2691694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norilsk camps |
E58415
|
entity |
| Predicate | inmates |
P41072
|
FINISHED |
| Object | political prisoners |
—
|
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: political prisoners | Statement: [Norilsk camps, inmates, political prisoners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inmates Context triple: [Norilsk camps, inmates, political prisoners]
-
A.
imprisonedWith
Indicates that two entities are confined or held in prison together at the same time and place.
-
B.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
C.
detainedPrisonersFrom
Indicates that an authority is holding prisoners who originate from or are associated with a specified place or source.
-
D.
usedForImprisoning
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
-
E.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda0cb9b48190ab354c277cef9e23 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81ea5d88190ab5c8f8b8064b931 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd879bb808190bd2c34de1664c816 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:54 p.m.