Triple
T1616940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angel Island State Park |
E34739
|
entity |
| Predicate | immigrationStationActiveYears |
P30464
|
FINISHED |
| Object | 1910–1940 |
—
|
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: 1910–1940 | Statement: [Angel Island State Park, immigrationStationActiveYears, 1910–1940]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: immigrationStationActiveYears Context triple: [Angel Island State Park, immigrationStationActiveYears, 1910–1940]
-
A.
yearOfImmigration
Indicates the specific year in which an entity immigrated to a new country or region.
-
B.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
C.
deportationYear
Indicates the year in which an entity was deported from a country or territory.
-
D.
yearOfPermanentResidency
Indicates the specific year in which an entity began or was granted permanent residency in a particular place.
-
E.
citizenshipGrantedYear
Indicates the specific year in which an entity was officially granted citizenship.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a93fedcb108190ad91f938d5eeaaa2 |
completed | March 5, 2026, 8:33 a.m. |
Created at: March 4, 2026, 7:28 p.m.