Triple
T7689410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | War Relocation Authority |
E174206
|
entity |
| Predicate | estimatedNumberOfPeopleAffected |
P54084
|
FINISHED |
| Object | over 110000 Japanese Americans |
—
|
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 110000 Japanese Americans | Statement: [War Relocation Authority, estimatedNumberOfPeopleAffected, over 110000 Japanese Americans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfPeopleAffected Context triple: [War Relocation Authority, estimatedNumberOfPeopleAffected, over 110000 Japanese Americans]
-
A.
estimatedAffectedPeople
chosen
Indicates the estimated number of people expected to be impacted by a particular event, condition, or action.
-
B.
affectedPeople
Indicates the people who are impacted or influenced by a particular event, action, or condition.
-
C.
estimatedVictimsUnderAuthority
Indicates that a specified authority is estimated to have a certain number of victims under its control, influence, or jurisdiction.
-
D.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
E.
estimatedNumberOfBeneficiaries
Indicates the approximate count of individuals or entities expected to receive benefits from something.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.