Triple
T11598399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alien Registration Act of 1940 |
E275062
|
entity |
| Predicate | approximateNumberRegistered |
P56974
|
FINISHED |
| Object | over 4 million aliens |
—
|
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 4 million aliens | Statement: [Alien Registration Act of 1940, approximateNumberRegistered, over 4 million aliens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberRegistered Context triple: [Alien Registration Act of 1940, approximateNumberRegistered, over 4 million aliens]
-
A.
registerCount
Indicates the number of registers associated with or allocated to a given entity in a system.
-
B.
estimatedMemberCount
chosen
Indicates the approximate or predicted number of members associated with an entity.
-
C.
userCount
Indicates the number of users associated with or involved in a given context or entity.
-
D.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
-
E.
serviceNumberApproximate
Indicates that one entity’s service number is approximately equal to, but not necessarily exactly the same as, another entity’s service number.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89549c870819086e16e9110bbad87 |
completed | April 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.