Triple
T8380862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weihsien Internment Camp |
E197683
|
entity |
| Predicate | numberOfInternees |
P13732
|
FINISHED |
| Object | over 2000 |
—
|
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 2000 | Statement: [Weihsien Internment Camp, numberOfInternees, over 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInternees Context triple: [Weihsien Internment Camp, numberOfInternees, over 2000]
-
A.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, or event.
-
B.
numberOfPrisonersApproximate
chosen
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
C.
numberOfExecutedAdults
Indicates the count of adult individuals who have been executed in a given context or event.
-
D.
numberOfAgents
Indicates the quantity of agents involved in or associated with a given entity or situation.
-
E.
estimatedPrisoners
Indicates a relationship where a value represents the estimated number of prisoners associated with a particular entity or context.
- 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_69ca82f64c188190af4e1608036b865d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80c57080819097eef2b7e46eaaee |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cfe82881909fe374ba52649e84 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:02 p.m.