Triple
T9388010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentine military dictatorship (National Reorganization Process) |
E225950
|
entity |
| Predicate | estimatedNumberOfDisappeared |
P87238
|
FINISHED |
| Object | between 10000 and 30000 |
—
|
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: between 10000 and 30000 | Statement: [Argentine military dictatorship (National Reorganization Process), estimatedNumberOfDisappeared, between 10000 and 30000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfDisappeared Context triple: [Argentine military dictatorship (National Reorganization Process), estimatedNumberOfDisappeared, between 10000 and 30000]
-
A.
missingPersonsEstimate
chosen
Indicates an estimated number of people who are unaccounted for or reported missing in a given context or event.
-
B.
yearOfDisappearance
Indicates the specific year in which an entity disappeared or ceased to be present.
-
C.
estimatedNumberEmancipated
Indicates the estimated count of individuals who have been emancipated.
-
D.
disappearedDuring
Indicates that an entity ceased to be observable or present during the time span or event associated with another entity.
-
E.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d6e5f081908102909cb4cbb649 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.