Triple
T622101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Trail |
E14534
|
entity |
| Predicate | estimatedEmigrants |
P17800
|
FINISHED |
| Object | hundreds of thousands of people |
—
|
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: hundreds of thousands of people | Statement: [California Trail, estimatedEmigrants, hundreds of thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedEmigrants Context triple: [California Trail, estimatedEmigrants, hundreds of thousands of people]
-
A.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
B.
immigratedTo
Indicates that an entity moved from its country of origin to live permanently in another specified country or region.
-
C.
yearOfEmigration
Indicates the specific year in which an entity permanently left its country or place of origin to settle elsewhere.
-
D.
displacedPeopleEstimate
Indicates an estimated number of people who have been forced to leave their homes or usual places of residence due to a particular event or situation.
-
E.
immigrantPopulationShare
Indicates the proportion of a total population that is made up of immigrants.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e402d9c8190936896e3ebb6edc5 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49d0069d0819087c83b608f6fc053 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49e2107548190af0c1d67cfa475d1 |
completed | March 1, 2026, 8:14 p.m. |
Created at: March 1, 2026, 7:35 p.m.