Triple
T317176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellis Island |
E7732
|
entity |
| Predicate | numberOfImmigrantsProcessed |
P11975
|
FINISHED |
| Object | over 12 million |
—
|
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 12 million | Statement: [Ellis Island, numberOfImmigrantsProcessed, over 12 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfImmigrantsProcessed Context triple: [Ellis Island, numberOfImmigrantsProcessed, over 12 million]
-
A.
yearOfImmigration
Indicates the specific year in which an entity immigrated to a new country or region.
-
B.
immigrantPopulationShare
Indicates the proportion of a total population that is made up of immigrants.
-
C.
immigratedTo
Indicates that an entity moved from its country of origin to live permanently in another specified country or region.
-
D.
majorImmigrationPeriod
Indicates that a time interval represents a significant period during which substantial immigration occurred.
-
E.
numberOfBorderGuards
Indicates the quantity of border guards associated with a given location, event, or entity.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea65ca7081908093e6aaaf2d34f7 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.