Triple
T17069423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American streamlined passenger trains |
E414173
|
entity |
| Predicate | introducedPeriod |
P60853
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [North American streamlined passenger trains, introducedPeriod, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedPeriod Context triple: [North American streamlined passenger trains, introducedPeriod, 1930s]
-
A.
introducedDuring
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
B.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
C.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
D.
approximateIntroductionPeriod
chosen
Indicates the approximate time period during which an entity was first introduced or came into use.
-
E.
establishedPeriod
Indicates the time span or date range during which something was founded, created, or formally brought into existence.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbfb1f08190807301ff6e573cf5 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.