Triple
T17159365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tydings–McDuffie Act |
E416434
|
entity |
| Predicate | immigrationQuotaForFilipinosPerYear |
P32335
|
FINISHED |
| Object | 50 |
—
|
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: 50 | Statement: [Tydings–McDuffie Act, immigrationQuotaForFilipinosPerYear, 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: immigrationQuotaForFilipinosPerYear Context triple: [Tydings–McDuffie Act, immigrationQuotaForFilipinosPerYear, 50]
-
A.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
B.
limitedImmigrationFrom
chosen
Indicates that an entity restricts or caps the number or conditions of immigrants coming from a specified source entity.
-
C.
immigrationQuotaBasis
Indicates the criterion or basis used to determine or allocate an immigration quota.
-
D.
increasedAnnualImmigrationCeiling
Indicates that the annual limit on immigration has been raised to allow more immigrants per year.
-
E.
yearOfImmigration
Indicates the specific year in which an entity immigrated to a new country or region.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f9103e3881908e76cea1c4880779 |
completed | April 18, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.